diff --git a/content/.metadata.json b/content/.metadata.json
index c83335fb97..d01a6d5e68 100644
--- a/content/.metadata.json
+++ b/content/.metadata.json
@@ -1,7 +1,7 @@
{
"metadata": {
"version": "2.0",
- "fetch_date": "2026-10-29T06:35:38.622893Z",
+ "fetch_date": "2026-10-29T17:09:28.821692Z",
"section": "all"
},
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@@ -6351,8 +6351,8 @@
"url": "https://code.claude.com/docs/en/plugins/mods/api",
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"path": "en/docs/claude-code/plugins/mods/api.md",
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{
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@@ -7471,8 +7471,8 @@
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{
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"size": 51636
},
+ {
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{
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"status": "success",
@@ -8850,8 +8857,8 @@
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{
"url": "https://modelcontextprotocol.io/specification/2024-11-05/architecture",
@@ -9928,8 +9935,8 @@
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{
"url": "https://support.claude.com/en/articles/8114494-how-up-to-date-is-claude-s-training-data",
@@ -10005,8 +10012,8 @@
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"url": "https://support.claude.com/en/articles/8241126-upload-files-to-claude",
@@ -10075,8 +10082,8 @@
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"url": "https://support.claude.com/en/articles/8325621-i-would-like-to-input-sensitive-data-into-my-chats-with-claude-who-can-view-my-conversations",
@@ -10138,8 +10145,8 @@
"url": "https://support.claude.com/en/articles/8887527-customizing-your-appearance-settings",
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{
"url": "https://support.claude.com/en/articles/8896518-does-anthropic-crawl-data-from-the-web-and-how-can-site-owners-block-the-crawler",
@@ -10313,8 +10320,8 @@
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{
"url": "https://support.claude.com/en/articles/10366376-how-can-i-delete-my-claude-console-account",
@@ -10656,8 +10663,8 @@
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@@ -10677,8 +10684,8 @@
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"url": "https://support.claude.com/en/articles/10684626-enable-and-use-web-search",
@@ -10705,8 +10712,8 @@
"url": "https://support.claude.com/en/articles/10949351-getting-started-with-local-mcp-servers-on-claude-desktop",
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"path": "support/10949351-getting-started-with-local-mcp-servers-on-claude-desktop.md",
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{
"url": "https://support.claude.com/en/articles/11049741-what-is-the-max-plan",
@@ -10740,8 +10747,8 @@
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{
"url": "https://support.claude.com/en/articles/11107691-why-is-a-coupon-or-promotion-not-available-for-my-account",
@@ -10873,7 +10880,7 @@
"url": "https://support.claude.com/en/articles/11725453-set-up-the-claude-lti-in-canvas-by-instructure",
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"url": "https://support.claude.com/en/articles/11817273-use-claude-s-chat-search-and-memory-to-build-on-previous-context",
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{
"url": "https://support.claude.com/en/articles/11818288-why-am-i-being-asked-to-verify-my-payment-method",
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"url": "https://support.claude.com/en/articles/11932705-automated-security-reviews-in-claude-code",
@@ -10964,14 +10971,14 @@
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"url": "https://support.claude.com/en/articles/12012173-get-started-with-claude-in-chrome",
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{
"url": "https://support.claude.com/en/articles/12109679-creating-a-new-account-after-deletion",
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"url": "https://support.claude.com/en/articles/12119250-model-safety-bug-bounty-program",
@@ -11027,21 +11034,21 @@
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{
"url": "https://support.claude.com/en/articles/12293051-use-claude-in-xcode",
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@@ -11111,7 +11118,7 @@
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"path": "github/claude-cookbooks/third_party/ElevenLabs/low_latency_stt_claude_tts.ipynb",
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"url": "https://raw.githubusercontent.com/anthropics/claude-cookbooks/main/third_party/VoyageAI/how_to_create_embeddings.md",
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"url": "https://raw.githubusercontent.com/anthropics/claude-cookbooks/main/tool_evaluation/tool_evaluation.ipynb",
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@@ -24467,15 +24474,15 @@
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"status": "success",
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"status": "success",
"path": "github/claude-cookbooks/tool_use/tool_choice.ipynb",
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{
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diff --git a/content/claude/cowork/changelog.md b/content/claude/cowork/changelog.md
index 1f8ab85c27..bcdb062f78 100644
--- a/content/claude/cowork/changelog.md
+++ b/content/claude/cowork/changelog.md
@@ -49,7 +49,7 @@ Bundled Claude Code version: 2.1.309.
* Added a warning in Cowork, Chat and Code once a person has used 75% of the token limit set with `inferenceMaxTokensPerWindow` and `inferenceTokenWindowHours`. Set `inferenceTokenWarningPercent` (1 to 100) to change the percent. At the limit it reads “Token limit reached” and cannot be closed.
* Changed `managedMcpServers` entries with `server: "github"` so that `pull_request_review_write` asks before every call, comment-only reviews and thread resolves included, even when `toolPolicy` allows it. Where no prompt can be shown, the call is refused. `toolPolicy` can still block it.
* Changed a failed `PreToolUse` or `PermissionRequest` hook with `"shell": "powershell"` to block the call on PCs without Git for Windows unless it sets `args` or `"onFailure": "continue"`. If written for Bash: remove `shell`, add `"onFailure": "block"` to keep blocking, install Git, reopen Claude.
-* Changed an unset `desktopHome` to open Unified Claude at launches after 12:00 PM PT on November 10, 2026. Where `coworkTabEnabled` is `false`, no feature turns on or off. With Cowork on, a set `chatSessionRetentionDays` without an equal `coworkSessionRetentionDays` keeps the current view.
+* Changed an unset `desktopHome` to open Unified Claude at launches after 12:00 PM PT on November 10, 2026. With Cowork on, a set `chatSessionRetentionDays` without an equal `coworkSessionRetentionDays` keeps the current view.
* Changed an unset `desktopHome` with Cowork on to also turn on Chat and Advanced file analysis when it starts to open Unified Claude (November 10, 2026), even if `chatTabEnabled` or `chatAdvancedFileAnalysisEnabled` is `false`.
* Changed Chat, Cowork and Code sessions to no longer start while Claude’s provider connection settings are missing, invalid or not yet fetched from your organization’s server. Claude says so at once.
* Changed the Microsoft 365 connector to keep each saved sign-in per `tenantId`, `clientId`, `azureCloud` and `continuousAccessEvaluation`. Connected users sign in again once after this update. Where `microsoftAuthDefaultAccount` is `enabled` on Windows, they get the account picker from then on.
diff --git a/content/claude/third-party/claude-desktop/configuration-changelog.md b/content/claude/third-party/claude-desktop/configuration-changelog.md
index 30e071610b..358325b6ce 100644
--- a/content/claude/third-party/claude-desktop/configuration-changelog.md
+++ b/content/claude/third-party/claude-desktop/configuration-changelog.md
@@ -28,7 +28,7 @@ Configuration keys by Claude Desktop release. Each section lists keys added in t
**Changed:**
-* `desktopHome`: from November 10, 2026 (12:00 PM PT, by the device's clock), an unset key opens Unified Claude at the app's next launch. Where `coworkTabEnabled` is not `false`, Chat and Advanced file analysis come on with Cowork, even if `chatTabEnabled` or `chatAdvancedFileAnalysisEnabled` is `false`. Where `coworkTabEnabled` is `false`, Cowork, Chat and Advanced file analysis stay on or off as they are today. A deployment with Cowork on that sets `chatSessionRetentionDays`, and does not set `coworkSessionRetentionDays` to the same number of days, keeps its current view. Earlier releases are unchanged.
+* `desktopHome`: from November 10, 2026 (12:00 PM PT, by the device's clock), an unset key opens Unified Claude at the app's next launch. With Cowork on, Chat and Advanced file analysis come on too, even if `chatTabEnabled` or `chatAdvancedFileAnalysisEnabled` is `false`. A deployment with Cowork on that sets `chatSessionRetentionDays`, and does not set `coworkSessionRetentionDays` to the same number of days, keeps its current view. Earlier releases are unchanged.
* `inferenceModels`: an entry accepts `behavesAs`, the Claude model behind a Model ID that Claude Desktop cannot identify, such as a gateway alias. The ID then gets that model's effort levels and limits. Once any entry sets it, sessions that Claude Desktop starts no longer read a person's own `modelPicker` setting from Claude Code's settings.
* `managedMcpServers`: a remote entry accepts `defaultState`. Set it to `"off"` and the connector stays out of each person's sessions until they turn it on under Connectors in the + menu. Adding `"off"` to a connector in use turns it off for everyone who has not switched it on.
* `managedMcpServers`: a remote entry's `oauth` accepts `omitResource`. Set it to `true` when the identity provider rejects the OAuth `resource` parameter (Microsoft Entra ID: AADSTS9010010). It needs the entry's client ID, a scope that names the API, and exactly one sign-in server: a tenant ID, one authorization server, or an authorization URL and token URL. Otherwise the server is not loaded.
diff --git a/content/claude/third-party/claude-desktop/configuration.md b/content/claude/third-party/claude-desktop/configuration.md
index 2986a6a9ff..5dcd0e1856 100644
--- a/content/claude/third-party/claude-desktop/configuration.md
+++ b/content/claude/third-party/claude-desktop/configuration.md
@@ -1566,7 +1566,7 @@ One of: `standard`, `off`
> **More detail**
>
-> `standard` turns on Unified Claude, which combines Chat and Cowork into one experience. `off` turns Chat and Cowork off entirely. `isClaudeCodeForDesktopEnabled` still decides Code. While the key is unset, `chatTabEnabled`, `chatAdvancedFileAnalysisEnabled`, and `coworkTabEnabled` decide until November 10, 2026 (12:00 PM PT). Current versions of Claude Desktop launched after that open Unified Claude for an unset key. Where `coworkTabEnabled` is not `false`, they read it as `standard`, whatever the other two say. Where it is `false`, Cowork stays off, and Chat and file analysis stay as the other two set them. Two cases keep those three keys deciding, as before that date. One: Cowork is allowed, `chatSessionRetentionDays` is set, and `coworkSessionRetentionDays` is not set to the same number of days. Two: Chat, Cowork, and `isClaudeCodeForDesktopEnabled` are all off, where the app turns one of them back on. Values are case-sensitive, so `Standard` is not recognized. A value that the app does not recognize is read as `off`, so update the app on devices before you deploy a value added in a later version.
+> `standard` turns on Unified Claude, which combines Chat and Cowork into one experience. `off` turns Chat and Cowork off entirely. `isClaudeCodeForDesktopEnabled` still decides Code. While the key is unset, `chatTabEnabled`, `chatAdvancedFileAnalysisEnabled`, and `coworkTabEnabled` decide until November 10, 2026 (12:00 PM PT). Current versions of Claude Desktop launched after that open Unified Claude for an unset key. With Cowork on, they read it as `standard`, whatever `chatTabEnabled` and `chatAdvancedFileAnalysisEnabled` say. Two cases keep those three keys deciding, as before that date. One: Cowork is on, `chatSessionRetentionDays` is set, and `coworkSessionRetentionDays` is not set to the same number of days. Two: Chat, Cowork, and `isClaudeCodeForDesktopEnabled` are all off, where the app turns one of them back on. Values are case-sensitive, so `Standard` is not recognized. A value that the app does not recognize is read as `off`, so update the app on devices before you deploy a value added in a later version.
***
diff --git a/content/en/docs/claude-code/plugins/mods/api.md b/content/en/docs/claude-code/plugins/mods/api.md
index de64f6dbd6..22b0cb1bfd 100644
--- a/content/en/docs/claude-code/plugins/mods/api.md
+++ b/content/en/docs/claude-code/plugins/mods/api.md
@@ -338,6 +338,7 @@ After the user stops a running turn, for example with Esc, some work your mod ha
| A recurring job scheduled with a tool such as CronCreate that comes due before the user's next input | Starts no turn then. The job loses that run and keeps its schedule. | Nothing needed |
| An event from a monitor your mod started | The monitor keeps running. An event the monitor raises before the user's next input is dropped, except the notice that the monitor ended, which arrives after that input. | Nothing can be done |
| A subagent your mod spawned and later resumed with `$.session.send` that finishes before the user's next input | Its finish notice waits, and reaches the conversation after that input | Nothing needed |
+| A foreground Bash or PowerShell command from `$.tool.call` that was already running when the user stopped the turn and reaches its timeout before their next input | Stopped at its timeout instead of [moving to the background](https://code.claude.com/docs/en/tools-reference.md#foreground-commands-that-move-to-the-background). The call resolves with `isError` set, and the output includes the line `Ended instead of moving to the background: plugins' input is held, by a Stop or by the host's limits.` | Run it again after the user's next input, as [Retry a refused or dropped call](#retry-a-refused-or-dropped-call) shows |
When a scheduled job comes due or a monitor raises an event before the user's next input, the user can see the [`Stopped:` toast](https://code.claude.com/docs/en/plugins/mods/troubleshoot#stopped-type-a-message-to-continue).
diff --git a/content/github/claude-cookbooks/CLAUDE.md b/content/github/claude-cookbooks/CLAUDE.md
index c06ad4e5e0..864ddd034d 100644
--- a/content/github/claude-cookbooks/CLAUDE.md
+++ b/content/github/claude-cookbooks/CLAUDE.md
@@ -65,13 +65,13 @@ style: lint/format
- Opus: `claude-opus-5-5`
- Sonnet: `claude-sonnet-5-5`
- Fable: `claude-fable-5-1`
- - Haiku: `claude-haiku-4-5`
+ - Haiku: `claude-haiku-5-5`
- **Never use dated model IDs** (e.g., `claude-sonnet-4-5-20250929`). Always use the non-dated alias.
- **Bedrock model IDs** follow a different format. Use the base Bedrock model ID from the docs:
- Opus 5.5: `anthropic.claude-opus-5-5`
- Sonnet 5.5: `anthropic.claude-sonnet-5-5`
- Fable 5.1: `anthropic.claude-fable-5-1`
- - Haiku 4.5: `anthropic.claude-haiku-4-5`
+ - Haiku 5.5: `anthropic.claude-haiku-5-5`
- Prepend `global.` for global endpoints (recommended): `global.anthropic.claude-opus-5-5`
- Note: these are the IDs for Bedrock's Messages-API endpoint. Integrations that only go through InvokeModel (for example `boto3` `invoke_model`, or fine-tuning jobs) use the dated form instead, e.g. `anthropic.claude-haiku-4-5-20251001-v1:0`.
diff --git a/content/github/claude-cookbooks/CONTRIBUTING.md b/content/github/claude-cookbooks/CONTRIBUTING.md
index d4498cb0d5..6dbae8bc9b 100644
--- a/content/github/claude-cookbooks/CONTRIBUTING.md
+++ b/content/github/claude-cookbooks/CONTRIBUTING.md
@@ -118,8 +118,8 @@ If a hook fails, fix the issues and try committing again.
2. **Use current Claude models**:
- Use model aliases for better maintainability when available
- - Current models: `claude-opus-5-5`, `claude-sonnet-5-5`, `claude-fable-5-1`, `claude-haiku-4-5`
- - Never use dated model IDs; `claude-haiku-4-5` is a good low-cost default for examples
+ - Current models: `claude-opus-5-5`, `claude-sonnet-5-5`, `claude-fable-5-1`, `claude-haiku-5-5`
+ - Never use dated model IDs; `claude-haiku-5-5` is a good low-cost default for examples
- Check current models at: https://platform.claude.com/docs/en/about-claude/models/overview
- Claude will automatically validate model usage in PR reviews
diff --git a/content/github/claude-cookbooks/capabilities/classification/evaluation/README.md b/content/github/claude-cookbooks/capabilities/classification/evaluation/README.md
index 871d9215f0..95fc805769 100644
--- a/content/github/claude-cookbooks/capabilities/classification/evaluation/README.md
+++ b/content/github/claude-cookbooks/capabilities/classification/evaluation/README.md
@@ -22,7 +22,7 @@ The evaluation is orchestrated by the `promptfooconfig.yaml` file. In this file
- The functions are identical to those used in `guide.ipynb` except that instead of calling the Claude API they just return the prompt. Promptfoo then handles the orchestration of calling the API and storing the results.
- You can read more about prompt functions [here](https://www.promptfoo.dev/docs/configuration/parameters#prompt-functions). Using python allows us to reuse the VectorDB class which is necessary for RAG, this is defined in `vectordb.py`.
- Providers
- - With Promptfoo you can connect to many different LLMs from different platforms, see [here for more](https://www.promptfoo.dev/docs/providers). In `guide.ipynb` we used Haiku with default temperature 0.0. We will use Promptfoo to experiment with an array of different temperature settings to identify the optimal choice for our use case.
+ - With Promptfoo you can connect to many different LLMs from different platforms, see [here for more](https://www.promptfoo.dev/docs/providers). In `guide.ipynb` we used Claude Haiku with default sampling settings. The checked-in Promptfoo configuration is the recorded temperature sweep on `claude-haiku-4-5`; current models reject a non-default `temperature`, so to re-run it on Claude Haiku 5.5 drop the `temperature` lines and compare models instead.
- Tests
- We will use the same data that was used in `guide.ipynb` which can be found in [`dataset.csv`](./dataset.csv).
- Promptfoo has a wide array of built in tests which can be found [here](https://www.promptfoo.dev/docs/configuration/expected-outputs/deterministic).
diff --git a/content/github/claude-cookbooks/capabilities/classification/guide.ipynb b/content/github/claude-cookbooks/capabilities/classification/guide.ipynb
index 794c0f04ea..c806dd7a12 100644
--- a/content/github/claude-cookbooks/capabilities/classification/guide.ipynb
+++ b/content/github/claude-cookbooks/capabilities/classification/guide.ipynb
@@ -56,7 +56,7 @@
"\n",
"import anthropic\n",
"\n",
- "MODEL = \"claude-haiku-4-5\"\n",
+ "MODEL = \"claude-haiku-5-5\"\n",
"client = anthropic.Anthropic(\n",
" # This is the default and can be omitted\n",
" api_key=os.getenv(\"ANTHROPIC_API_KEY\"),\n",
@@ -483,9 +483,9 @@
"\n",
"1. **Structured prompt template**: We provide the category definitions and the support ticket in a clear XML format, making it easy for Claude to parse the information.\n",
"\n",
- "2. **Controlled output with prefilling**: By starting the assistant's response with `` and setting `stop_sequences=[\"\"]`, we force Claude to output just the category label—no explanation or extra text. This makes response parsing reliable and deterministic.\n",
+ "2. **Controlled output with tags and a stop sequence**: The prompt asks for the label between `` tags and we set `stop_sequences=[\"\"]`, so Claude stops right after the label. We then take whatever follows `` in the text blocks of the response, which keeps parsing reliable.\n",
"\n",
- "3. **Deterministic classification**: Setting `temperature=0.0` ensures consistent predictions for the same input, which is critical for classification tasks.\n"
+ "3. **Default sampling**: current Claude models, including Claude Haiku 5.5, do not accept `temperature`, `top_p`, or `top_k`, so we leave sampling at its defaults. The constrained output format keeps predictions consistent.\n"
]
},
{
@@ -513,19 +513,16 @@
" .replace(\"{{ticket}}\", X)\n",
" )\n",
" response = client.messages.create(\n",
- " messages=[\n",
- " {\"role\": \"user\", \"content\": prompt},\n",
- " {\"role\": \"assistant\", \"content\": \"\"},\n",
- " ],\n",
+ " messages=[{\"role\": \"user\", \"content\": prompt}],\n",
" stop_sequences=[\"\"],\n",
" max_tokens=4096,\n",
- " temperature=0.0,\n",
" model=MODEL,\n",
" )\n",
"\n",
- " # Extract the result from the response\n",
- " result = response.content[0].text # pyright: ignore[reportAttributeAccessIssue]\n",
- " return result.strip()"
+ " # The reply is \"Label\" (the stop sequence trims the closing tag) and may be\n",
+ " # preceded by a thinking block, so read only the text blocks and take what follows the tag.\n",
+ " text = \"\".join(b.text for b in response.content if b.type == \"text\")\n",
+ " return text.split(\"\")[-1].strip()"
]
},
{
@@ -785,19 +782,14 @@
" .replace(\"{{examples}}\", rag_string)\n",
" )\n",
" response = client.messages.create(\n",
- " messages=[\n",
- " {\"role\": \"user\", \"content\": prompt},\n",
- " {\"role\": \"assistant\", \"content\": \"\"},\n",
- " ],\n",
+ " messages=[{\"role\": \"user\", \"content\": prompt}],\n",
" stop_sequences=[\"\"],\n",
" max_tokens=4096,\n",
- " temperature=0.0,\n",
- " model=\"claude-haiku-4-5\",\n",
+ " model=MODEL,\n",
" )\n",
"\n",
- " # Extract the result from the response\n",
- " result = response.content[0].text.strip()\n",
- " return result"
+ " text = \"\".join(b.text for b in response.content if b.type == \"text\")\n",
+ " return text.split(\"\")[-1].strip()"
]
},
{
@@ -920,19 +912,16 @@
" .replace(\"{{examples}}\", rag_string)\n",
" )\n",
" response = client.messages.create(\n",
- " messages=[\n",
- " {\"role\": \"user\", \"content\": prompt},\n",
- " {\"role\": \"assistant\", \"content\": \"\"},\n",
- " ],\n",
+ " messages=[{\"role\": \"user\", \"content\": prompt}],\n",
" stop_sequences=[\"\"],\n",
" max_tokens=4096,\n",
- " temperature=0.0,\n",
" model=MODEL,\n",
" )\n",
"\n",
- " # Extract the result from the response\n",
- " result = response.content[0].text.split(\"\")[1].strip()\n",
- " return result"
+ " # The prompt asks for ...Label;\n",
+ " # take what follows in the text blocks.\n",
+ " text = \"\".join(b.text for b in response.content if b.type == \"text\")\n",
+ " return text.split(\"\")[-1].strip()"
]
},
{
@@ -1023,7 +1012,7 @@
"\n",
"## Running Promptfoo Evaluation\n",
"\n",
- "Promptfoo is an open-source LLM evaluation toolkit that automates prompt testing across multiple configurations. For this guide, we've set up a Promptfoo evaluation that tests all three approaches (Simple, RAG, RAG w/ CoT) across different temperature settings.\n",
+ "Promptfoo is an open-source LLM evaluation toolkit that automates prompt testing across multiple configurations. For this guide, we've set up a Promptfoo evaluation that tests all three approaches (Simple, RAG, RAG w/ CoT). The checked-in configuration and `data/results.csv` were recorded with `claude-haiku-4-5` across five temperature settings; current models no longer accept `temperature`, so to re-run it on Claude Haiku 5.5 drop the `temperature` lines and compare models instead.\n",
"\n",
"**To run the evaluation:**\n",
"\n",
@@ -1105,7 +1094,7 @@
"### What We Tested\n",
"\n",
"Using Promptfoo, we evaluated all three prompt approaches (Simple, RAG, RAG w/ CoT) across:\n",
- "- **Multiple temperature settings** (0.0, 0.2, 0.4, 0.6, 0.8): Testing whether deterministic classification (T=0.0) outperforms slightly randomized outputs\n",
+ "- **Multiple temperature settings** (0.0, 0.2, 0.4, 0.6, 0.8), recorded with `claude-haiku-4-5`: testing whether deterministic classification (T=0.0) outperforms slightly randomized outputs. Current models do not accept `temperature`, so this axis only applies to that recorded run.\n",
"- **The same test set** (68 examples): Ensuring fair comparison across all configurations\n",
"- **Automated pass/fail checking**: Each prediction is automatically compared against ground truth labels\n",
"\n",
@@ -1119,7 +1108,7 @@
"\n",
"3. **Simple prompts are temperature-agnostic**: The simple classifier hovers around 70% accuracy regardless of temperature, confirming that without RAG or CoT, the model relies primarily on category definitions\n",
"\n",
- "4. **Production recommendation**: Use `temperature=0.0` with RAG w/ CoT for maximum consistency and accuracy (95.59%)\n",
+ "4. **Production recommendation**: Use RAG w/ CoT (95.59% in the recorded run) for the best accuracy; on current models leave sampling at its defaults\n",
"\n",
"To run these evaluations yourself, see `./evaluation/README.md` for setup instructions."
]
diff --git a/content/github/claude-cookbooks/capabilities/contextual-embeddings/guide.ipynb b/content/github/claude-cookbooks/capabilities/contextual-embeddings/guide.ipynb
index b0594907ac..e613d8a500 100644
--- a/content/github/claude-cookbooks/capabilities/contextual-embeddings/guide.ipynb
+++ b/content/github/claude-cookbooks/capabilities/contextual-embeddings/guide.ipynb
@@ -130,7 +130,7 @@
"metadata": {},
"outputs": [],
"source": [
- "MODEL_NAME = \"claude-haiku-4-5\""
+ "MODEL_NAME = \"claude-haiku-5-5\""
]
},
{
@@ -610,7 +610,7 @@
"2. Subsequent chunks: Read the document from cache (90% discount on those tokens)\n",
"3. Cache lasts 5 minutes, plenty of time to process all chunks in a document\n",
"\n",
- "**Cost example**: For 800-token chunks in 8k-token documents with 100 tokens of generated context, the total cost is $1.02 per million document tokens. You'll see the cache savings in the logs when you run the code below.\n",
+ "**Cost example**: For 800-token chunks in 8k-token documents with 100 tokens of generated context, the total cost in the recorded run (an earlier Haiku model) was $1.02 per million document tokens; expect a different figure at current Claude Haiku 5.5 prices. You'll see the cache savings in the logs when you run the code below.\n",
"\n",
"**Note:** Some embedding models have fixed input token limits. If you see worse performance with contextual embeddings, your contextualized chunks may be getting truncated—consider using an embedding model with a larger context window."
]
@@ -663,8 +663,7 @@
"def situate_context(doc: str, chunk: str) -> str:\n",
" response = client.messages.create(\n",
" model=MODEL_NAME,\n",
- " max_tokens=1024,\n",
- " temperature=0.0,\n",
+ " max_tokens=2048,\n",
" messages=[\n",
" {\n",
" \"role\": \"user\",\n",
@@ -693,7 +692,8 @@
"chunk_content = jsonl_data[0][\"golden_chunks\"][0][\"content\"]\n",
"\n",
"response = situate_context(doc_content, chunk_content)\n",
- "print(f\"Situated context: {response.content[0].text}\")\n",
+ "situated = \"\".join(b.text for b in response.content if b.type == \"text\")\n",
+ "print(f\"Situated context: {situated}\")\n",
"print(\"-\" * 10)\n",
"# Print cache performance metrics\n",
"print(f\"Input tokens: {response.usage.input_tokens}\")\n",
@@ -777,8 +777,7 @@
"\n",
" response = self.anthropic_client.messages.create(\n",
" model=MODEL_NAME,\n",
- " max_tokens=1000,\n",
- " temperature=0.0,\n",
+ " max_tokens=2048,\n",
" messages=[\n",
" {\n",
" \"role\": \"user\",\n",
@@ -799,7 +798,8 @@
" ],\n",
" extra_headers={\"anthropic-beta\": \"prompt-caching-2024-07-31\"},\n",
" )\n",
- " return response.content[0].text, response.usage\n",
+ " text = \"\".join(b.text for b in response.content if b.type == \"text\")\n",
+ " return text, response.usage\n",
"\n",
" def load_data(self, dataset: list[dict[str, Any]], parallel_threads: int = 1):\n",
" if self.embeddings and self.metadata:\n",
@@ -981,7 +981,7 @@
"\n",
"- We processed **737 chunks** across 9 codebase files\n",
"- **61.83% of input tokens** were read from cache (2.27M tokens at 90% discount)\n",
- "- Without caching, this would cost **~$9.20** in input tokens\n",
+ "- In the recorded run (an earlier Haiku model), without caching this would cost **~$9.20** in input tokens\n",
"- With caching, the actual cost drops to **~$2.85** (69% savings)\n",
"\n",
"The cache hit rate depends on how many chunks each document contains. Files with more chunks benefit more from caching since we write the full document to cache once, then read it repeatedly for each chunk in that file. This is why processing documents sequentially (rather than randomly shuffling chunks) is crucial for maximizing cache efficiency.\n",
diff --git a/content/github/claude-cookbooks/capabilities/knowledge_graph/evaluation/README.md b/content/github/claude-cookbooks/capabilities/knowledge_graph/evaluation/README.md
index 00019bc7c5..3e4cd1603f 100644
--- a/content/github/claude-cookbooks/capabilities/knowledge_graph/evaluation/README.md
+++ b/content/github/claude-cookbooks/capabilities/knowledge_graph/evaluation/README.md
@@ -25,7 +25,7 @@ uv run python capabilities/knowledge_graph/evaluation/eval_extraction.py
## Expected baseline
-With `claude-haiku-4-5` and the extraction prompt from the guide, expect roughly:
+The ranges below were recorded with `claude-haiku-4-5` and the extraction prompt from the guide; the script now defaults to `claude-haiku-5-5`, so re-run it to refresh them:
| Metric | P | R | F1 |
|---|---|---|---|
diff --git a/content/github/claude-cookbooks/capabilities/knowledge_graph/guide.ipynb b/content/github/claude-cookbooks/capabilities/knowledge_graph/guide.ipynb
index 74009a38b4..c5a217b81b 100644
--- a/content/github/claude-cookbooks/capabilities/knowledge_graph/guide.ipynb
+++ b/content/github/claude-cookbooks/capabilities/knowledge_graph/guide.ipynb
@@ -37,14 +37,7 @@
{
"cell_type": "code",
"execution_count": 1,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2026-03-25T19:26:42.140920Z",
- "iopub.status.busy": "2026-03-25T19:26:42.140857Z",
- "iopub.status.idle": "2026-03-25T19:26:42.413415Z",
- "shell.execute_reply": "2026-03-25T19:26:42.412964Z"
- }
- },
+ "metadata": {},
"outputs": [],
"source": [
"%%capture\n",
@@ -54,14 +47,7 @@
{
"cell_type": "code",
"execution_count": 2,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2026-03-25T19:26:42.414988Z",
- "iopub.status.busy": "2026-03-25T19:26:42.414909Z",
- "iopub.status.idle": "2026-03-25T19:26:43.240655Z",
- "shell.execute_reply": "2026-03-25T19:26:43.240146Z"
- }
- },
+ "metadata": {},
"outputs": [],
"source": [
"import json\n",
@@ -80,7 +66,7 @@
"load_dotenv()\n",
"client = anthropic.Anthropic()\n",
"\n",
- "EXTRACTION_MODEL = \"claude-haiku-4-5\"\n",
+ "EXTRACTION_MODEL = \"claude-haiku-5-5\"\n",
"SYNTHESIS_MODEL = \"claude-sonnet-5-5\""
]
},
@@ -105,14 +91,7 @@
{
"cell_type": "code",
"execution_count": 3,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2026-03-25T19:26:43.241827Z",
- "iopub.status.busy": "2026-03-25T19:26:43.241729Z",
- "iopub.status.idle": "2026-03-25T19:26:44.204180Z",
- "shell.execute_reply": "2026-03-25T19:26:44.203746Z"
- }
- },
+ "metadata": {},
"outputs": [
{
"name": "stdout",
@@ -121,7 +100,7 @@
"Loaded 6 documents\n",
"\n",
"Sample — Apollo program:\n",
- "The Apollo program, also known as Project Apollo, was the United States human spaceflight program led by NASA, which landed the first humans on the Moon in 1969. Apollo was conceived during Project Mercury and executed after Project Gemini. It was conceived in 1960 as a three-person spacecraft durin...\n"
+ "The Apollo program, also known as Project Apollo, was the United States human spaceflight program led by NASA, which landed the first humans on the Moon in 1969. The Apollo program was conceived in 1960 in the Dwight D. Eisenhower presidency during Project Mercury and executed after Project Gemini. ...\n"
]
}
],
@@ -173,14 +152,7 @@
{
"cell_type": "code",
"execution_count": 4,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2026-03-25T19:26:44.217932Z",
- "iopub.status.busy": "2026-03-25T19:26:44.217804Z",
- "iopub.status.idle": "2026-03-25T19:26:44.220838Z",
- "shell.execute_reply": "2026-03-25T19:26:44.220428Z"
- }
- },
+ "metadata": {},
"outputs": [],
"source": [
"EntityType = Literal[\"PERSON\", \"ORGANIZATION\", \"LOCATION\", \"EVENT\", \"ARTIFACT\"]\n",
@@ -220,7 +192,7 @@
"def extract(text: str) -> ExtractedGraph:\n",
" response = client.messages.parse(\n",
" model=EXTRACTION_MODEL,\n",
- " max_tokens=2048,\n",
+ " max_tokens=4096,\n",
" messages=[{\"role\": \"user\", \"content\": EXTRACTION_PROMPT.format(text=text)}],\n",
" output_format=ExtractedGraph,\n",
" )\n",
@@ -230,57 +202,20 @@
{
"cell_type": "code",
"execution_count": 5,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2026-03-25T19:26:44.222081Z",
- "iopub.status.busy": "2026-03-25T19:26:44.222008Z",
- "iopub.status.idle": "2026-03-25T19:27:06.258416Z",
- "shell.execute_reply": "2026-03-25T19:27:06.258001Z"
- }
- },
+ "metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Apollo program 8 entities 7 relations\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Apollo 11 6 entities 5 relations\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Neil Armstrong 3 entities 2 relations\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Saturn V 5 entities 4 relations\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Buzz Aldrin 6 entities 6 relations\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Kennedy Space Center 8 entities 10 relations\n",
- "\n",
- "Total: 36 raw entities, 34 raw relations\n"
+ "Apollo program 7 entities 6 relations\n",
+ "Apollo 11 7 entities 6 relations\n",
+ "Neil Armstrong 3 entities 3 relations\n",
+ "Saturn V 6 entities 6 relations\n",
+ "Buzz Aldrin 8 entities 10 relations\n",
+ "Kennedy Space Center 9 entities 13 relations\n",
+ "\n",
+ "Total: 40 raw entities, 44 raw relations\n"
]
}
],
@@ -315,51 +250,44 @@
{
"cell_type": "code",
"execution_count": 6,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2026-03-25T19:27:06.259683Z",
- "iopub.status.busy": "2026-03-25T19:27:06.259607Z",
- "iopub.status.idle": "2026-03-25T19:27:06.261870Z",
- "shell.execute_reply": "2026-03-25T19:27:06.261550Z"
- }
- },
+ "metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"ARTIFACT (3):\n",
- " Launch Complex 39\n",
+ " Lunar Module Eagle\n",
" Saturn V\n",
" Skylab\n",
"\n",
- "EVENT (11):\n",
+ "EVENT (13):\n",
+ " Apollo\n",
" Apollo 11\n",
" Apollo program\n",
+ " Artemis\n",
" Gemini 12\n",
" Project Gemini\n",
" Project Mercury\n",
- " Skylab program\n",
- " Space Shuttle program\n",
+ " Skylab\n",
+ " Space Shuttle\n",
"\n",
- "LOCATION (5):\n",
+ "LOCATION (9):\n",
+ " Cape Canaveral Space Force Station\n",
+ " Kennedy Space Center Launch Complex 39\n",
" Merritt Island\n",
" Moon\n",
"\n",
- "ORGANIZATION (7):\n",
- " Cape Canaveral Space Force Station\n",
+ "ORGANIZATION (6):\n",
" John F. Kennedy Space Center\n",
" NASA\n",
- " U.S. Congress\n",
"\n",
- "PERSON (10):\n",
+ "PERSON (9):\n",
" Buzz Aldrin\n",
" Dwight D. Eisenhower\n",
" Edwin Aldrin\n",
- " Jim Lovell\n",
" John F. Kennedy\n",
" Michael Collins\n",
- " Neil Alden Armstrong\n",
" Neil Armstrong\n",
"\n"
]
@@ -393,14 +321,7 @@
{
"cell_type": "code",
"execution_count": 7,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2026-03-25T19:27:06.262916Z",
- "iopub.status.busy": "2026-03-25T19:27:06.262844Z",
- "iopub.status.idle": "2026-03-25T19:27:06.265627Z",
- "shell.execute_reply": "2026-03-25T19:27:06.265309Z"
- }
- },
+ "metadata": {},
"outputs": [],
"source": [
"class Cluster(BaseModel):\n",
@@ -429,7 +350,7 @@
"\n",
" response = client.messages.parse(\n",
" model=SYNTHESIS_MODEL,\n",
- " max_tokens=2048,\n",
+ " max_tokens=4096,\n",
" messages=[\n",
" {\n",
" \"role\": \"user\",\n",
@@ -451,43 +372,35 @@
{
"cell_type": "code",
"execution_count": 8,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2026-03-25T19:27:06.266715Z",
- "iopub.status.busy": "2026-03-25T19:27:06.266650Z",
- "iopub.status.idle": "2026-03-25T19:27:19.255462Z",
- "shell.execute_reply": "2026-03-25T19:27:19.255102Z"
- }
- },
+ "metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Entity resolution: 24 unique names → 22 canonical entities\n",
+ "Entity resolution: 23 unique names → 21 canonical entities\n",
"\n",
"EVENT Apollo 11\n",
- "EVENT Apollo program\n",
+ "EVENT Apollo program (also: Apollo)\n",
+ "EVENT Artemis\n",
"PERSON Buzz Aldrin (also: Edwin Aldrin)\n",
- "ORGANIZATION Cape Canaveral Space Force Station\n",
+ "LOCATION Cape Canaveral Space Force Station\n",
"PERSON Dwight D. Eisenhower\n",
"EVENT Gemini 12\n",
- "PERSON Jim Lovell\n",
"PERSON John F. Kennedy\n",
"ORGANIZATION John F. Kennedy Space Center\n",
- "ARTIFACT Launch Complex 39\n",
+ "LOCATION Kennedy Space Center Launch Complex 39\n",
+ "ARTIFACT Lunar Module Eagle\n",
"LOCATION Merritt Island\n",
"PERSON Michael Collins\n",
"LOCATION Moon\n",
"ORGANIZATION NASA\n",
- "PERSON Neil Alden Armstrong (also: Neil Armstrong)\n",
+ "PERSON Neil Armstrong\n",
"EVENT Project Gemini\n",
"EVENT Project Mercury\n",
"ARTIFACT Saturn V\n",
"ARTIFACT Skylab\n",
- "EVENT Skylab program\n",
- "EVENT Space Shuttle program\n",
- "ORGANIZATION U.S. Congress\n"
+ "EVENT Space Shuttle\n"
]
}
],
@@ -535,28 +448,21 @@
{
"cell_type": "code",
"execution_count": 9,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2026-03-25T19:27:19.256729Z",
- "iopub.status.busy": "2026-03-25T19:27:19.256651Z",
- "iopub.status.idle": "2026-03-25T19:27:19.259946Z",
- "shell.execute_reply": "2026-03-25T19:27:19.259622Z"
- }
- },
+ "metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "Graph: 22 nodes, 34 edges\n",
+ "Graph: 21 nodes, 44 edges\n",
"Connected components: 1\n",
"\n",
"Most connected entities:\n",
- " Apollo program degree 9 (EVENT)\n",
- " Apollo 11 degree 9 (EVENT)\n",
- " John F. Kennedy Space Center degree 7 (ORGANIZATION)\n",
- " Neil Alden Armstrong degree 5 (PERSON)\n",
- " Buzz Aldrin degree 5 (PERSON)\n"
+ " Apollo 11 degree 12 (EVENT)\n",
+ " Apollo program degree 11 (EVENT)\n",
+ " John F. Kennedy Space Center degree 9 (ORGANIZATION)\n",
+ " Moon degree 7 (LOCATION)\n",
+ " NASA degree 6 (ORGANIZATION)\n"
]
}
],
@@ -597,23 +503,21 @@
{
"cell_type": "code",
"execution_count": 10,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2026-03-25T19:27:19.260882Z",
- "iopub.status.busy": "2026-03-25T19:27:19.260816Z",
- "iopub.status.idle": "2026-03-25T19:27:19.450313Z",
- "shell.execute_reply": "2026-03-25T19:27:19.449865Z"
- }
- },
+ "metadata": {},
"outputs": [
{
"data": {
- "image/png": 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"text/plain": [
""
]
},
- "metadata": {},
+ "metadata": {
+ "image/png": {
+ "height": 988,
+ "width": 1389
+ }
+ },
"output_type": "display_data"
}
],
@@ -668,14 +572,7 @@
{
"cell_type": "code",
"execution_count": 11,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2026-03-25T19:27:19.451695Z",
- "iopub.status.busy": "2026-03-25T19:27:19.451561Z",
- "iopub.status.idle": "2026-03-25T19:27:19.454885Z",
- "shell.execute_reply": "2026-03-25T19:27:19.454496Z"
- }
- },
+ "metadata": {},
"outputs": [],
"source": [
"class TimeRange(BaseModel):\n",
@@ -720,7 +617,7 @@
"\n",
" response = client.messages.parse(\n",
" model=SYNTHESIS_MODEL,\n",
- " max_tokens=1500,\n",
+ " max_tokens=4096,\n",
" messages=[\n",
" {\n",
" \"role\": \"user\",\n",
@@ -737,68 +634,52 @@
{
"cell_type": "code",
"execution_count": 12,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2026-03-25T19:27:19.455817Z",
- "iopub.status.busy": "2026-03-25T19:27:19.455755Z",
- "iopub.status.idle": "2026-03-25T19:27:38.133364Z",
- "shell.execute_reply": "2026-03-25T19:27:38.133013Z"
- }
- },
+ "metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "═══ Apollo program ═══\n",
- "The Apollo program, also known as Project Apollo, was a United States human spaceflight program led by NASA, primarily aimed at landing humans on the Moon. It was conceived in 1960 during the presidency of Dwight D. Eisenhower as a three-person spacecraft program, building upon the foundations laid by Project Mercury. The program was later formally dedicated to President John F. Kennedy's national goal, announced before the U.S. Congress on May 25, 1961, of landing a man on the Moon and returning him safely to Earth. Apollo followed Project Gemini in NASA's sequential human spaceflight efforts.\n",
- "\n",
- "The Apollo program successfully landed the first humans on the Moon in 1969. It relied on the Saturn V, a super heavy-lift launch vehicle developed by NASA specifically for the program, which flew from 1967 to 1973 and supported nine crewed flights to the Moon. Launch operations were conducted from Launch Complex 39 at Kennedy Space Center on Merritt Island, Florida, which has served as NASA's primary launch center since 1968.\n",
+ "═══ Apollo 11 ═══\n",
+ "Apollo 11 was the American spaceflight that first landed humans on the Moon. It was the fifth crewed mission of NASA's Apollo program, conducted by NASA, and took place in 1969. The Lunar Module Eagle was part of the mission. The crew was Commander Neil Armstrong, Command Module Pilot Michael Collins, and Lunar Module Pilot Edwin Buzz Aldrin. All three were on their second and final spaceflight. Armstrong became the first person to walk on the Moon, and Aldrin was the second. Aldrin had earlier made three spacewalks on NASA's 1966 Gemini 12 mission. Armstrong died in 2012 and Collins in 2021, which leaves Aldrin as the last surviving Apollo 11 crew member and the oldest living astronaut.\n",
"\n",
- "Time range: 1960 – 1973\n",
+ "Time range: 1969 – 1969\n",
"Key facts:\n",
- " • The Apollo program was conceived in 1960 under the presidency of Dwight D. Eisenhower as a three-person spacecraft program.\n",
- " • Apollo was dedicated to President John F. Kennedy's goal of landing a man on the Moon, as stated in his address to Congress on May 25, 1961.\n",
- " • The Apollo program successfully landed the first humans on the Moon in 1969.\n",
- " • The Saturn V rocket, developed under the Apollo program, flew from 1967 to 1973 and supported nine crewed lunar flights.\n",
- " • Launch operations for the Apollo program were carried out from Kennedy Space Center Launch Complex 39.\n",
- "\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "═══ Apollo 11 ═══\n",
- "Apollo 11 was the American spaceflight that achieved the historic first crewed lunar landing, representing the fifth crewed mission of NASA's Apollo program. The mission was commanded by Neil Armstrong, with Michael Collins serving as Command Module Pilot and Edwin \"Buzz\" Aldrin as Lunar Module Pilot. All three crew members were on their second and final spaceflights.\n",
+ " • Apollo 11 was the first spaceflight to land humans on the Moon.\n",
+ " • Apollo 11 was the fifth crewed mission of NASA's Apollo program.\n",
+ " • The crew was Neil Armstrong (Commander), Michael Collins (Command Module Pilot) and Buzz Aldrin (Lunar Module Pilot), each on their second and final spaceflight.\n",
+ " • Neil Armstrong, commander of Apollo 11, became the first person to walk on the Moon, followed by Buzz Aldrin as the second.\n",
+ " • Aldrin is the last surviving Apollo 11 crew member following the deaths of Armstrong in 2012 and Collins in 2021.\n",
"\n",
- "During the mission, Neil Armstrong became the first person to walk on the Moon, followed by Buzz Aldrin, making him the second. Michael Collins remained in the Command Module in lunar orbit. The mission stands as a landmark achievement in human spaceflight history. As of 2025, Buzz Aldrin is the last surviving crew member of Apollo 11, following the deaths of Armstrong in 2012 and Collins in 2021.\n",
+ "═══ Apollo program ═══\n",
+ "The Apollo program, also known as Project Apollo, was the United States human spaceflight program led by NASA. It landed the first humans on the Moon in 1969. It was conceived in 1960 during the Eisenhower presidency, while Project Mercury was under way, and was executed after Project Gemini. It was later dedicated to President John F. Kennedy's goal, stated in his May 25, 1961 address to Congress, of landing a man on the Moon and returning him safely to the Earth before the decade was out.\n",
"\n",
- "Time range: 1969 – 1969\n",
+ "Apollo 11 was the first mission to land humans on the Moon and the fifth crewed mission of the program. Its crew was Neil Armstrong, Michael Collins and Edwin \"Buzz\" Aldrin. The Saturn V, a three-stage, liquid-fueled, human-rated super heavy-lift rocket, was developed under the program for lunar exploration. Nine of the thirteen Saturn V launches sent 24 astronauts toward the Moon, from Apollo 8 to Apollo 17.\n",
+ "\n",
+ "Launch operations for Apollo were carried out from Kennedy Space Center Launch Complex 39 and managed by the Kennedy Space Center on Merritt Island, Florida. The sources do not state an exact end date for the program.\n",
+ "\n",
+ "Time range: 1960 – unknown\n",
"Key facts:\n",
- " • Apollo 11 was the fifth crewed mission of NASA's Apollo program and the first to land humans on the Moon.\n",
- " • The crew consisted of Commander Neil Armstrong, Command Module Pilot Michael Collins, and Lunar Module Pilot Buzz Aldrin.\n",
- " • Neil Armstrong was the first person to walk on the Moon, with Buzz Aldrin becoming the second.\n",
- " • All three Apollo 11 crew members were on their second and final spaceflights.\n",
- " • Buzz Aldrin is the last surviving member of the Apollo 11 crew, following the deaths of Armstrong in 2012 and Collins in 2021.\n",
- "\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
+ " • The Apollo program was the U.S. human spaceflight program led by NASA, and it landed the first humans on the Moon in 1969.\n",
+ " • The program was conceived in 1960 during the Eisenhower presidency and executed after Project Gemini.\n",
+ " • Apollo 11, crewed by Neil Armstrong, Michael Collins and Buzz Aldrin, was the fifth crewed Apollo mission and the first to land humans on the Moon.\n",
+ " • The Saturn V rocket was developed under the Apollo program, and nine of its thirteen launches carried 24 astronauts toward the Moon from Apollo 8 to Apollo 17.\n",
+ " • Apollo launch operations were carried out from Kennedy Space Center Launch Complex 39 and managed by the Kennedy Space Center.\n",
+ "\n",
"═══ John F. Kennedy Space Center ═══\n",
- "The John F. Kennedy Space Center (KSC) is a NASA field center situated on Merritt Island, Florida, on the east coast of the state. It is one of ten field centers operated by NASA and has served as the agency's primary launch center for American spaceflight, research, and technology since 1968. Launch operations for several major human spaceflight programs, including Apollo, Skylab, and the Space Shuttle, were conducted from KSC's Launch Complex 39 and managed by the center.\n",
+ "The John F. Kennedy Space Center (KSC) is one of the ten field centers of NASA. It is located on Merritt Island, on the east coast of Florida. Since 1968, KSC has served as NASA's primary launch center for American spaceflight, research, and technology.\n",
+ "\n",
+ "Launch operations for the Apollo, Skylab, Space Shuttle, and Artemis programs were carried out from Kennedy Space Center Launch Complex 39 and managed by KSC. Launch Complex 39 is part of the center.\n",
"\n",
- "KSC operates in close proximity to Cape Canaveral Space Force Station (CCSFS), with the two entities maintaining a collaborative relationship. Their management teams work closely together, share resources, and operate facilities on each other's property, reflecting a high degree of integration between the two installations.\n",
+ "KSC is adjacent to Cape Canaveral Space Force Station (CCSFS). The management of the two entities works closely together, shares resources, and operates facilities on each other's property.\n",
"\n",
"Time range: 1968 – ongoing\n",
"Key facts:\n",
- " • John F. Kennedy Space Center is located on Merritt Island, Florida, and is one of ten NASA field centers.\n",
- " • KSC has been NASA's primary launch center for American spaceflight, research, and technology since 1968.\n",
- " • Launch operations for the Apollo, Skylab, and Space Shuttle programs were carried out from KSC's Launch Complex 39.\n",
- " • KSC is adjacent to Cape Canaveral Space Force Station, and the two entities share resources and operate facilities on each other's property.\n",
+ " • The John F. Kennedy Space Center is one of the ten field centers of NASA.\n",
+ " • KSC is located on Merritt Island, Florida, on the east coast of the state.\n",
+ " • Since 1968, KSC has been NASA's primary launch center of American spaceflight, research, and technology.\n",
+ " • Launch operations for the Apollo, Skylab, Space Shuttle, and Artemis programs were carried out from Launch Complex 39 and managed by KSC.\n",
+ " • KSC is adjacent to Cape Canaveral Space Force Station; the two share resources and operate facilities on each other's property.\n",
"\n"
]
}
@@ -832,14 +713,7 @@
{
"cell_type": "code",
"execution_count": 13,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2026-03-25T19:27:38.134715Z",
- "iopub.status.busy": "2026-03-25T19:27:38.134643Z",
- "iopub.status.idle": "2026-03-25T19:27:38.137431Z",
- "shell.execute_reply": "2026-03-25T19:27:38.137167Z"
- }
- },
+ "metadata": {},
"outputs": [],
"source": [
"def serialize_subgraph(center: str, hops: int = 2) -> str:\n",
@@ -869,7 +743,7 @@
" prompt = question\n",
" response = client.messages.create(\n",
" model=SYNTHESIS_MODEL,\n",
- " max_tokens=500,\n",
+ " max_tokens=4096, # leaves room for adaptive thinking before the answer\n",
" messages=[{\"role\": \"user\", \"content\": prompt}],\n",
" )\n",
" text_block = next((b for b in response.content if b.type == \"text\"), None)\n",
@@ -881,14 +755,7 @@
{
"cell_type": "code",
"execution_count": 14,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2026-03-25T19:27:38.138472Z",
- "iopub.status.busy": "2026-03-25T19:27:38.138416Z",
- "iopub.status.idle": "2026-03-25T19:27:47.877335Z",
- "shell.execute_reply": "2026-03-25T19:27:47.877002Z"
- }
- },
+ "metadata": {},
"outputs": [
{
"name": "stdout",
@@ -896,79 +763,57 @@
"text": [
"Querying 2-hop neighborhood of: Apollo program\n",
"\n",
- "WITHOUT graph context:\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "# Locations Connected to Apollo 11 Personnel\n",
- "\n",
- "## Neil Armstrong (Commander)\n",
- "\n",
- "- **Wapakoneta, Ohio** – birthplace and hometown; the **Neil Armstrong Air & Space Museum** is located there\n",
- "- **Purdue University, Indiana** – where he studied aeronautical engineering\n",
- "- **Edwards Air Force Base, California** – where he worked as a test pilot\n",
- "- **Cincinnati, Ohio** – where he lived later in life and died (2012)\n",
+ "WITHOUT graph context:\n",
+ "# Locations linked to Apollo 11 people\n",
"\n",
- "## Buzz Aldrin (Lunar Module Pilot)\n",
+ "I've grouped these by connection type, focusing mainly on the three crew members, with a few others at the end.\n",
"\n",
- "- **Montclair, New Jersey** – birthplace\n",
- "- **West Point, New York** – attended the U.S. Military Academy\n",
- "- **MIT, Massachusetts** – earned his doctorate in astronautics\n",
- "- **Los Angeles area** – longtime residence after NASA career\n",
+ "## Birthplaces and hometowns\n",
+ "- **Wapakoneta, Ohio**: Neil Armstrong's hometown, now home to the Armstrong Air & Space Museum.\n",
+ "- **Glen Ridge and Montclair, New Jersey**: Buzz Aldrin was born in Glen Ridge and attended Montclair High School.\n",
+ "- **Rome, Italy**: Michael Collins was born here, where his father was a U.S. Army officer.\n",
"\n",
- "## Michael Collins (Command Module Pilot)\n",
+ "## Education and military training\n",
+ "- **Purdue University (Indiana)**: Armstrong studied aeronautical engineering here.\n",
+ "- **U.S. Military Academy, West Point (New York)**: Both Aldrin and Collins graduated from here.\n",
+ "- **MIT (Massachusetts)**: Aldrin earned his doctorate in astronautics, with a thesis on orbital rendezvous.\n",
+ "- **Korea**: Armstrong flew Navy combat missions, and Aldrin flew Air Force combat missions.\n",
"\n",
- "- **Rome, Italy** – birthplace (son of a U.S. Army officer)\n",
- "- **Washington, D.C.** – attended school; later directed the **Smithsonian National Air and Space Museum**\n",
- "- **West Point** – attended the Military Academy\n",
+ "## Careers before and after Apollo\n",
+ "- **Edwards Air Force Base / NASA Flight Research Center (California)**: Armstrong was a research test pilot here, and Collins attended the test pilot school.\n",
+ "- **Lewis Research Center (Cleveland, Ohio)**: Armstrong's early NASA work.\n",
+ "- **Washington, D.C.**: Collins became the director of the National Air and Space Museum.\n",
+ "- **University of Cincinnati**: Armstrong taught aerospace engineering here after leaving NASA.\n",
"\n",
- "## Shared/Mission Locations\n",
+ "## Mission sites\n",
+ "- **Kennedy Space Center, Launch Complex 39A (Florida)**: The launch site on July 16, 1969.\n",
+ "- **Tranquility Base (Sea of Tranquility, Moon)**: Armstrong and Aldrin's landing site.\n",
+ "- **Johnson Space Center / Mission Control (Houston)**: The flight controllers' base, including Flight Director Gene Kranz and capsule communicator Charlie Duke.\n",
+ "- **Tracking stations**: Goldstone (California), Honeysuckle Creek and Parkes Observatory (Australia). Parkes and Honeysuckle Creek were crucial for relaying the moonwalk TV broadcast.\n",
+ "- **Pacific Ocean, southwest of Hawaii**: The splashdown site, where the USS *Hornet* recovered the crew.\n",
+ "- **Honolulu and Houston**: The crew was quarantined, first in a mobile unit aboard the *Hornet* and then at the Lunar Receiving Laboratory.\n",
"\n",
- "- **Kennedy Space Center, Florida** – launch site (July 16, 1969)\n",
- "- **Houston, Texas** – Mission Control and astronaut training (Johnson Space Center)\n",
- "- **Pacific Ocean** – splashdown and recovery site\n",
- "- **Honolulu, Hawaii** – where the crew was initially quarantined aboard the USS Hornet\n",
+ "## Later life and death\n",
+ "- **Armstrong** lived near Lebanon, Ohio, and died in Cincinnati in 2012. He was buried at sea in the Philippine Sea.\n",
+ "- **Collins** retired in Florida (Naples and Marco Island area), died in 2021, and is buried at Arlington National Cemetery.\n",
+ "- **Aldrin** has lived in California and Florida, and remains an advocate for Mars exploration.\n",
"\n",
- "Would you like more detail on any individual?\n",
+ "If you're interested in a particular person or type of place (for example mission control staff, or a travel itinerary of museums and sites), I can go deeper.\n",
"\n",
"────────────────────────────────────────────────────────────\n",
"\n",
- "WITH graph context:\n"
- ]
- },
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "## Locations Connected to Apollo 11 Personnel\n",
- "\n",
- "Based on the knowledge graph, here is what can be determined about people connected to Apollo 11 and their location relationships:\n",
- "\n",
- "### Neil Alden Armstrong\n",
- "Neil Armstrong is the person directly identified as part of Apollo 11, supported by:\n",
- "- **(Apollo 11) --[commanded by]--> (Neil Alden Armstrong)**\n",
- "- **(Neil Alden Armstrong) --[commanded]--> (Apollo 11)**\n",
+ "WITH graph context:\n",
+ "**The Moon is the only location directly linked to Apollo 11 people in the graph.**\n",
"\n",
- "He is connected to the following location:\n",
+ "**Direct connections**\n",
+ "- Buzz Aldrin: `(Buzz Aldrin) --[walked on]--> (Moon)`. He is tied to Apollo 11 by `(Buzz Aldrin) --[crewed]--> (Apollo 11)` and `--[part of]--> (Apollo 11)`.\n",
+ "- Neil Armstrong: `(Neil Armstrong) --[walked on]--> (Moon)`. He is tied to Apollo 11 by `(Neil Armstrong) --[commanded]--> (Apollo 11)`. The graph has no explicit \"part of\" edge for him, but commanding the mission implies he was part of it.\n",
"\n",
- "#### 🌕 The Moon\n",
- "- **(Neil Alden Armstrong) --[walked on]--> (Moon)**\n",
+ "**Indirect connections**\n",
+ "- Michael Collins: `(Michael Collins) --[crewed]--> (Apollo 11)` and `--[part of]--> (Apollo 11)`. The graph has no edge linking him directly to a location. He connects to the Moon only through the mission: `(Apollo 11) --[landed on]--> (Moon)`.\n",
+ "- Through the Apollo program, the crew is also loosely connected to Kennedy Space Center and its site. The chain is `(Apollo 11) --[part of]--> (Apollo program)`, then `(John F. Kennedy Space Center) --[managed launch operations for]--> (Apollo program)` and `(Kennedy Space Center Launch Complex 39) --[launched]--> (Apollo program)`. From there, `(John F. Kennedy Space Center) --[located on]--> (Merritt Island)` and `--[adjacent to]--> (Cape Canaveral Space Force Station)`. These links run through the program, not through the people themselves.\n",
"\n",
- "This is the only **direct** person-to-location edge in the graph for an Apollo 11 crew member.\n",
- "\n",
- "---\n",
- "\n",
- "### Indirect Location Connection via Apollo 11 itself:\n",
- "Apollo 11 as a mission is also connected to the Moon:\n",
- "- **(Apollo 11) --[landed on]--> (Moon)**\n",
- "\n",
- "---\n",
- "\n",
- "### Limitations\n",
- "The knowledge graph does **not** include location data for any other Apollo 11 crew members (e.g., Buzz Aldrin or Michael Collins), so no connections can be drawn for them. The only person-location relationship supported by the graph is **Neil Armstrong → walked on → the Moon**.\n"
+ "**Not locations:** Aldrin also `--[piloted]--> (Lunar Module Eagle)`, which is `--[part of]--> (Apollo 11)`, and `--[piloted]--> (Gemini 12)`. These are spacecraft and missions, not places.\n"
]
}
],
@@ -1013,14 +858,7 @@
{
"cell_type": "code",
"execution_count": 15,
- "metadata": {
- "execution": {
- "iopub.execute_input": "2026-03-25T19:27:47.878729Z",
- "iopub.status.busy": "2026-03-25T19:27:47.878660Z",
- "iopub.status.idle": "2026-03-25T19:27:47.883302Z",
- "shell.execute_reply": "2026-03-25T19:27:47.883000Z"
- }
- },
+ "metadata": {},
"outputs": [
{
"name": "stdout",
@@ -1028,8 +866,8 @@
"text": [
"Raw extraction vs resolved-graph recall against gold:\n",
"\n",
- "Apollo 11 raw F1=0.71 (P=1.00 R=0.55) resolved R=0.55\n",
- " still missed after resolution: apollo program, columbia, kennedy space center, lunar module eagle, saturn v\n",
+ "Apollo 11 raw F1=0.78 (P=1.00 R=0.64) resolved R=0.64\n",
+ " still missed after resolution: columbia, kennedy space center, lunar module eagle, saturn v\n",
"Neil Armstrong raw F1=0.55 (P=1.00 R=0.38) resolved R=0.38\n",
" still missed after resolution: gemini 8, korean war, nasa, purdue university, united states navy\n"
]
@@ -1137,7 +975,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.11.13"
+ "version": "3.12.3"
}
},
"nbformat": 4,
diff --git a/content/github/claude-cookbooks/capabilities/retrieval_augmented_generation/evaluation/README.md b/content/github/claude-cookbooks/capabilities/retrieval_augmented_generation/evaluation/README.md
index 88ecde19d6..ed903ace57 100644
--- a/content/github/claude-cookbooks/capabilities/retrieval_augmented_generation/evaluation/README.md
+++ b/content/github/claude-cookbooks/capabilities/retrieval_augmented_generation/evaluation/README.md
@@ -32,7 +32,7 @@ The evaluation is orchestrated by the `promptfooconfig...` `.yaml` files. In our
- The functions are identical to those used in `guide.ipynb` except that instead of calling the Claude API they just return the prompt. Promptfoo then handles the orchestration of calling the API and storing the results.
- You can read more about prompt functions [here](https://www.promptfoo.dev/docs/configuration/parameters#prompt-functions). Using python allows us to reuse the VectorDB class which is necessary for RAG, this is defined in `vectordb.py`.
- Providers
- - With Promptfoo you can connect to many different LLMs from different platforms, see [here for more](https://www.promptfoo.dev/docs/providers). In `guide.ipynb` we used Haiku with default temperature 0.0. We will use Promptfoo to experiment with different models.
+ - With Promptfoo you can connect to many different LLMs from different platforms, see [here for more](https://www.promptfoo.dev/docs/providers). In `guide.ipynb` we used Claude Haiku with default sampling settings. We will use Promptfoo to experiment with different models.
- Tests
- We will use the same data that was used in `guide.ipynb`. We split it into `end_to_end_dataset.csv` and `retrieval_dataset.csv` and added an `__expected` column to each dataset which allows us to automatically run assertions for each row
- Promptfoo has a wide array of built in tests which can be found [here](https://www.promptfoo.dev/docs/configuration/expected-outputs/deterministic).
diff --git a/content/github/claude-cookbooks/capabilities/retrieval_augmented_generation/guide.ipynb b/content/github/claude-cookbooks/capabilities/retrieval_augmented_generation/guide.ipynb
index 8095436e93..58b9679844 100644
--- a/content/github/claude-cookbooks/capabilities/retrieval_augmented_generation/guide.ipynb
+++ b/content/github/claude-cookbooks/capabilities/retrieval_augmented_generation/guide.ipynb
@@ -359,10 +359,9 @@
" Answer the question now, and avoid providing preamble such as 'Here is the answer', etc\n",
" \"\"\"\n",
" response = client.messages.create(\n",
- " model=\"claude-haiku-4-5\",\n",
+ " model=\"claude-haiku-5-5\",\n",
" max_tokens=2500,\n",
" messages=[{\"role\": \"user\", \"content\": prompt}],\n",
- " temperature=0,\n",
" )\n",
" return get_text(response)"
]
@@ -3302,10 +3301,9 @@
" \"\"\"\n",
"\n",
" response = client.messages.create(\n",
- " model=\"claude-haiku-4-5\",\n",
- " max_tokens=150,\n",
+ " model=\"claude-haiku-5-5\",\n",
+ " max_tokens=1024,\n",
" messages=[{\"role\": \"user\", \"content\": prompt}],\n",
- " temperature=0,\n",
" )\n",
"\n",
" summary = get_text(response).strip()\n",
@@ -3502,10 +3500,9 @@
" Answer the question now, and avoid providing preamble such as 'Here is the answer', etc\n",
" \"\"\"\n",
" response = client.messages.create(\n",
- " model=\"claude-haiku-4-5\",\n",
+ " model=\"claude-haiku-5-5\",\n",
" max_tokens=2500,\n",
" messages=[{\"role\": \"user\", \"content\": prompt}],\n",
- " temperature=0,\n",
" )\n",
" return get_text(response)"
]
@@ -6022,19 +6019,16 @@
" \"\"\"\n",
" try:\n",
" response = client.messages.create(\n",
- " model=\"claude-haiku-4-5\",\n",
- " max_tokens=50,\n",
- " messages=[\n",
- " {\"role\": \"user\", \"content\": prompt},\n",
- " {\"role\": \"assistant\", \"content\": \"\"},\n",
- " ],\n",
- " temperature=0,\n",
+ " model=\"claude-haiku-5-5\",\n",
+ " max_tokens=1024,\n",
+ " messages=[{\"role\": \"user\", \"content\": prompt}],\n",
" stop_sequences=[\"\"],\n",
" )\n",
"\n",
- " # Extract the indices from the response\n",
+ " # The reply is \"1, 4, 7\" (the stop sequence trims the closing tag);\n",
+ " # keep only what follows the opening tag.\n",
" response_text = get_text(response).strip()\n",
- " indices_str = response_text\n",
+ " indices_str = response_text.split(\"\")[-1].strip()\n",
" relevant_indices = []\n",
" for idx in indices_str.split(\",\"):\n",
" try:\n",
@@ -6102,10 +6096,9 @@
" Answer the question now, and avoid providing preamble such as 'Here is the answer', etc\n",
" \"\"\"\n",
" response = client.messages.create(\n",
- " model=\"claude-haiku-4-5\",\n",
+ " model=\"claude-haiku-5-5\",\n",
" max_tokens=2500,\n",
" messages=[{\"role\": \"user\", \"content\": prompt}],\n",
- " temperature=0,\n",
" )\n",
" return get_text(response)"
]
diff --git a/content/github/claude-cookbooks/capabilities/summarization/evaluation/README.md b/content/github/claude-cookbooks/capabilities/summarization/evaluation/README.md
index a082c63df9..87eb2bff75 100644
--- a/content/github/claude-cookbooks/capabilities/summarization/evaluation/README.md
+++ b/content/github/claude-cookbooks/capabilities/summarization/evaluation/README.md
@@ -42,7 +42,7 @@ Prompts:
Providers:
- We configure different Claude versions and their settings here.
-- This allows us to test across multiple models or with varying parameters (e.g., different temperature settings).
+- This allows us to test across multiple models or with varying parameters (e.g., different `max_tokens` or effort settings).
Tests:
diff --git a/content/github/claude-cookbooks/capabilities/summarization/guide.ipynb b/content/github/claude-cookbooks/capabilities/summarization/guide.ipynb
index 357633e92f..67eb6766ba 100644
--- a/content/github/claude-cookbooks/capabilities/summarization/guide.ipynb
+++ b/content/github/claude-cookbooks/capabilities/summarization/guide.ipynb
@@ -780,7 +780,7 @@
" # We use guided_legal_summary here, but you can use basic_summarize or any other summarization function\n",
" # Note that we'll also use Haiku for the interim summaries, and Sonnet for the final summary\n",
" chunk_summaries = [\n",
- " guided_sublease_summary(chunk, model=\"claude-haiku-4-5\", max_tokens=max_tokens)\n",
+ " guided_sublease_summary(chunk, model=\"claude-haiku-5-5\", max_tokens=max_tokens)\n",
" for chunk in chunks\n",
" ]\n",
"\n",
@@ -921,12 +921,13 @@
" prompt = f\"Legal document summary: {summary}\\n\\nLegal query: {query}\\n\\nRate the relevance of this legal document to the query on a scale of 0 to 10. Only output the numeric value:\"\n",
"\n",
" response = client.messages.create(\n",
- " model=\"claude-haiku-4-5\",\n",
- " max_tokens=2,\n",
- " temperature=0,\n",
+ " model=\"claude-haiku-5-5\",\n",
+ " max_tokens=1024,\n",
+ " output_config={\"effort\": \"low\"},\n",
" messages=[{\"role\": \"user\", \"content\": prompt}],\n",
" )\n",
- " ranked_score = float(get_text(response))\n",
+ " match = re.search(r\"\\d+(?:\\.\\d+)?\", get_text(response))\n",
+ " ranked_score = float(match.group()) if match else 0.0\n",
" ranked_scores.append(ranked_score)\n",
"\n",
" ranked_indices = np.argsort(ranked_scores)[::-1][:top_k]\n",
@@ -1342,7 +1343,7 @@
"1. Analyze the Promptfoo results to identify strengths and weaknesses – for example, it seems our contains eval was failing a lot. This is probably because some of the documents don't contain the information which is required in the XML tags. We should refine this eval if we are to accurately assess performance (but this is just an example!).\n",
"2. Refine prompts to address specific issues (e.g., improve conciseness or completeness) – we saw that multi-shot was an initial really good first attempt. This is somethign we should incorporate alongside some of the advanced techniques to improve performance further.\n",
"3. Experiment with different chunking strategies for long documents.\n",
- "4. Tune the `max_tokens` parameter (sampling parameters such as `temperature` are not supported on current Sonnet and Opus models).\n",
+ "4. Tune the `max_tokens` parameter (sampling parameters such as `temperature` are not supported on current Claude models).\n",
"5. Implement post-processing steps to enhance summary quality.\n",
"\n",
"## Conclusion and Best Practices\n",
diff --git a/content/github/claude-cookbooks/claude_agent_sdk/01_The_chief_of_staff_agent.ipynb b/content/github/claude-cookbooks/claude_agent_sdk/01_The_chief_of_staff_agent.ipynb
index 5324e09a5c..eaf1940cb0 100644
--- a/content/github/claude-cookbooks/claude_agent_sdk/01_The_chief_of_staff_agent.ipynb
+++ b/content/github/claude-cookbooks/claude_agent_sdk/01_The_chief_of_staff_agent.ipynb
@@ -9,7 +9,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "📋 Notebook configured to use: claude-opus-4-6\n"
+ "📋 Notebook configured to use: claude-opus-5-5\n"
]
}
],
@@ -2721,7 +2721,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.12.9"
+ "version": "3.12.3"
}
},
"nbformat": 4,
diff --git a/content/github/claude-cookbooks/claude_agent_sdk/05_Building_a_session_browser.ipynb b/content/github/claude-cookbooks/claude_agent_sdk/05_Building_a_session_browser.ipynb
index 1b64f67b0f..684e1ab392 100644
--- a/content/github/claude-cookbooks/claude_agent_sdk/05_Building_a_session_browser.ipynb
+++ b/content/github/claude-cookbooks/claude_agent_sdk/05_Building_a_session_browser.ipynb
@@ -79,7 +79,7 @@
"\n",
"load_dotenv()\n",
"\n",
- "MODEL = \"claude-haiku-4-5\"\n",
+ "MODEL = \"claude-haiku-5-5\"\n",
"\n",
"# All demo sessions live under this project directory. Using a dedicated\n",
"# cwd keeps the demo isolated from your real Claude Code sessions.\n",
diff --git a/content/github/claude-cookbooks/managed_agents/CMA_with_mongodb_atlas.ipynb b/content/github/claude-cookbooks/managed_agents/CMA_with_mongodb_atlas.ipynb
index 8cfc910c38..2df8fc2850 100644
--- a/content/github/claude-cookbooks/managed_agents/CMA_with_mongodb_atlas.ipynb
+++ b/content/github/claude-cookbooks/managed_agents/CMA_with_mongodb_atlas.ipynb
@@ -100,7 +100,7 @@
"`MDB_ATLAS_API_KEY` (the MongoDB Atlas AI endpoint, serving both `/v1/embeddings` and\n",
"`/v1/rerank`) or `VOYAGE_API_KEY` (the `voyageai` SDK). `ENABLE_RERANK=1` adds the reranker\n",
"second stage. `AUTO_APPROVE=1` resolves the human gate deterministically for CI. `COOKBOOK_MODEL`\n",
- "overrides the agent model (default `claude-haiku-4-5`).\n",
+ "overrides the agent model (default `claude-haiku-5-5`).\n",
"\n",
"**No Atlas cluster yet?** The partner notebook [`rag_using_mongodb.ipynb`](../third_party/MongoDB/rag_using_mongodb.ipynb) walks through creating a free cluster and getting your `MONGO_URI`; the [Atlas Search index docs](https://www.mongodb.com/docs/atlas/atlas-search/create-index/) cover index setup."
]
diff --git a/content/github/claude-cookbooks/misc/building_moderation_filter.ipynb b/content/github/claude-cookbooks/misc/building_moderation_filter.ipynb
index 34e6e93ce8..712ca2738c 100644
--- a/content/github/claude-cookbooks/misc/building_moderation_filter.ipynb
+++ b/content/github/claude-cookbooks/misc/building_moderation_filter.ipynb
@@ -54,14 +54,14 @@
},
{
"cell_type": "code",
- "execution_count": 2,
+ "execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from anthropic import Anthropic\n",
"\n",
"client = Anthropic()\n",
- "MODEL_NAME = \"claude-haiku-4-5\"\n",
+ "MODEL_NAME = \"claude-haiku-5-5\"\n",
"\n",
"\n",
"def moderate_text(user_text, guidelines):\n",
@@ -80,15 +80,15 @@
" prompt = prompt_template.format(user_text=user_text, guidelines=guidelines)\n",
"\n",
" # Send the prompt to Claude and get the response\n",
- " response = (\n",
- " client.messages.create(\n",
- " model=MODEL_NAME, max_tokens=10, messages=[{\"role\": \"user\", \"content\": prompt}]\n",
- " )\n",
- " .content[0]\n",
- " .text\n",
+ " response = client.messages.create(\n",
+ " model=MODEL_NAME,\n",
+ " max_tokens=1024,\n",
+ " output_config={\"effort\": \"low\"},\n",
+ " messages=[{\"role\": \"user\", \"content\": prompt}],\n",
" )\n",
"\n",
- " return response"
+ " # Read the text block by type: the response may start with a thinking block\n",
+ " return \"\".join(block.text for block in response.content if block.type == \"text\").strip()"
]
},
{
@@ -100,7 +100,7 @@
},
{
"cell_type": "code",
- "execution_count": 3,
+ "execution_count": 2,
"metadata": {},
"outputs": [
{
@@ -157,7 +157,7 @@
},
{
"cell_type": "code",
- "execution_count": 4,
+ "execution_count": 3,
"metadata": {},
"outputs": [
{
@@ -221,7 +221,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 4,
"metadata": {},
"outputs": [
{
@@ -229,7 +229,7 @@
"output_type": "stream",
"text": [
"\n",
- "The post appears to be promoting a band rather than discussing rollercoasters, theme parks, or the amusement industry. This falls under the \"spam, advertisements, or self-promotion\" category, which is grounds for blocking the post.\n",
+ "The post promotes a band called \"Coaster Shredders\" and asks readers to check out its YouTube channel. That is self-promotion, which the BLOCK guidelines name explicitly. The band name contains a rollercoaster reference, but the post does not discuss coasters, parks, rides, or the amusement industry. It contains no violence, hate speech, or illegal content. The promotional nature is the deciding factor.\n",
"\n",
"\n",
"\n"
@@ -258,15 +258,12 @@
"\n",
"user_post = \"Introducing my new band - Coaster Shredders. Check us out on YouTube!!\"\n",
"\n",
- "response = (\n",
- " client.messages.create(\n",
- " model=MODEL_NAME,\n",
- " max_tokens=1000,\n",
- " messages=[{\"role\": \"user\", \"content\": cot_prompt.format(user_post=user_post)}],\n",
- " )\n",
- " .content[0]\n",
- " .text\n",
+ "response = client.messages.create(\n",
+ " model=MODEL_NAME,\n",
+ " max_tokens=2048,\n",
+ " messages=[{\"role\": \"user\", \"content\": cot_prompt.format(user_post=user_post)}],\n",
")\n",
+ "response = \"\".join(block.text for block in response.content if block.type == \"text\")\n",
"\n",
"print(response)"
]
@@ -281,7 +278,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 5,
"metadata": {},
"outputs": [
{
@@ -328,15 +325,12 @@
"\n",
"user_post = \"Why Boomerang Coasters Ain't It (Don't @ Me)\"\n",
"\n",
- "response = (\n",
- " client.messages.create(\n",
- " model=MODEL_NAME,\n",
- " max_tokens=1000,\n",
- " messages=[{\"role\": \"user\", \"content\": examples_prompt.format(user_text=user_post)}],\n",
- " )\n",
- " .content[0]\n",
- " .text\n",
+ "response = client.messages.create(\n",
+ " model=MODEL_NAME,\n",
+ " max_tokens=2048,\n",
+ " messages=[{\"role\": \"user\", \"content\": examples_prompt.format(user_text=user_post)}],\n",
")\n",
+ "response = \"\".join(block.text for block in response.content if block.type == \"text\")\n",
"\n",
"print(response)"
]
@@ -358,7 +352,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.11.4"
+ "version": "3.12.3"
}
},
"nbformat": 4,
diff --git a/content/github/claude-cookbooks/misc/how_to_enable_json_mode.ipynb b/content/github/claude-cookbooks/misc/how_to_enable_json_mode.ipynb
index 90d9b0d7fc..128f9f5dae 100644
--- a/content/github/claude-cookbooks/misc/how_to_enable_json_mode.ipynb
+++ b/content/github/claude-cookbooks/misc/how_to_enable_json_mode.ipynb
@@ -13,7 +13,7 @@
"id": "model-note-prefill",
"metadata": {},
"source": [
- "> **Model note:** this notebook uses `claude-haiku-4-5` because assistant-message prefill (the technique shown below) is only accepted on Claude Haiku 4.5 among current models; Claude Opus 5.5, Claude Sonnet 5.5, and Claude Fable 5.1 return a 400 for it. For guaranteed JSON on those models, use [structured outputs](https://platform.claude.com/docs/en/build-with-claude/structured-outputs) (`output_config.format` with a JSON schema) instead."
+ "> **Model note:** this notebook uses `claude-haiku-4-5`, a legacy model, because assistant-message prefill (the technique shown below) is only accepted on Claude Haiku 4.5. All current models (Claude Opus 5.5, Claude Sonnet 5.5, Claude Fable 5.1, and Claude Haiku 5.5) return a 400 for a request that ends with an assistant message. For guaranteed JSON on current models, use [structured outputs](https://platform.claude.com/docs/en/build-with-claude/structured-outputs) (`output_config.format` with a JSON schema) instead; the tag-and-stop-sequence techniques later in this notebook also work on every model."
]
},
{
@@ -64,7 +64,8 @@
"outputs": [],
"source": [
"client = Anthropic()\n",
- "# See the model note at the top: prefill (used below) is only accepted on Claude Haiku 4.5.\n",
+ "# See the model note at the top: prefill (used below) is only accepted on the legacy\n",
+ "# Claude Haiku 4.5; current models, including Claude Haiku 5.5, return a 400 for it.\n",
"MODEL_NAME = \"claude-haiku-4-5\""
]
},
diff --git a/content/github/claude-cookbooks/misc/metaprompt.ipynb b/content/github/claude-cookbooks/misc/metaprompt.ipynb
index 9c4477ad64..754a758d53 100644
--- a/content/github/claude-cookbooks/misc/metaprompt.ipynb
+++ b/content/github/claude-cookbooks/misc/metaprompt.ipynb
@@ -60,7 +60,7 @@
"# The model that writes your prompt template.\n",
"MODEL_NAME = \"claude-sonnet-5-5\"\n",
"# The (faster, cheaper) model used to test the generated prompt at the end.\n",
- "TEST_MODEL_NAME = \"claude-haiku-4-5\"\n",
+ "TEST_MODEL_NAME = \"claude-haiku-5-5\"\n",
"# Maximum response length for both API calls (any thinking the model does counts toward it).\n",
"MAX_TOKENS = 8192\n",
"client = anthropic.Anthropic()"
diff --git a/content/github/claude-cookbooks/misc/read_web_pages_with_haiku.ipynb b/content/github/claude-cookbooks/misc/read_web_pages_with_haiku.ipynb
index 198d77db60..356719e221 100644
--- a/content/github/claude-cookbooks/misc/read_web_pages_with_haiku.ipynb
+++ b/content/github/claude-cookbooks/misc/read_web_pages_with_haiku.ipynb
@@ -4,7 +4,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "# Summarizing Web Page Content with Claude Haiku 4.5\n",
+ "# Summarizing Web Page Content with Claude Haiku\n",
"In this recipe, we'll learn how to fetch the content of a web page given its URL and then use Anthropic's Claude API to generate a summary of the page's content.\n",
"\n",
"Let's start by installing the Anthropic library."
@@ -30,7 +30,7 @@
},
{
"cell_type": "code",
- "execution_count": 6,
+ "execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
@@ -39,7 +39,7 @@
"\n",
"# Set up the Claude API client\n",
"client = Anthropic()\n",
- "MODEL_NAME = \"claude-haiku-4-5\""
+ "MODEL_NAME = \"claude-haiku-5-5\""
]
},
{
@@ -52,10 +52,25 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 2,
"metadata": {},
"outputs": [],
- "source": "import requests\n\nurl = \"https://en.wikipedia.org/wiki/96th_Academy_Awards\"\nresponse = requests.get(url, timeout=30)\n\nif response.status_code == 200:\n page_content = response.text\nelse:\n print(f\"Failed to fetch the web page. Status code: {response.status_code}\")\n exit(1)"
+ "source": [
+ "import requests\n",
+ "\n",
+ "url = \"https://en.wikipedia.org/wiki/96th_Academy_Awards\"\n",
+ "# Wikimedia asks clients to send an identifying User-Agent; the default python-requests one is refused (403)\n",
+ "headers = {\n",
+ " \"User-Agent\": \"claude-cookbook-example/1.0 (https://github.com/anthropics/claude-cookbooks)\"\n",
+ "}\n",
+ "response = requests.get(url, headers=headers, timeout=30)\n",
+ "\n",
+ "if response.status_code == 200:\n",
+ " page_content = response.text\n",
+ "else:\n",
+ " print(f\"Failed to fetch the web page. Status code: {response.status_code}\")\n",
+ " exit(1)"
+ ]
},
{
"cell_type": "markdown",
@@ -67,7 +82,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
@@ -88,25 +103,36 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
- "The 96th Academy Awards ceremony took place on March 10, 2024 at the Dolby Theatre in Los Angeles. The ceremony, hosted by Jimmy Kimmel, presented Academy Awards (Oscars) in 23 categories honoring films released in 2023. \n",
+ "**96th Academy Awards (Wikipedia article)**\n",
+ "\n",
+ "The 96th Academy Awards ceremony, presented by the Academy of Motion Picture Arts and Sciences, was held on March 10, 2024, at the Dolby Theatre in Hollywood, Los Angeles. It honored films released in 2023 and was hosted by Jimmy Kimmel, his fourth time hosting. The telecast was produced by Raj Kapoor and Katy Mullan, directed by Hamish Hamilton, and aired on ABC.\n",
+ "\n",
+ "Key points:\n",
"\n",
- "The big winner of the night was the film \"Oppenheimer,\" which won a leading 7 awards including Best Picture, Best Director for Christopher Nolan, and several technical awards. Other major winners were \"Poor Things\" with 4 awards and \"The Zone of Interest\" with 2 awards. Several notable records and milestones were set, including Steven Spielberg receiving his 13th Best Picture nomination, and Billie Eilish and Finneas O'Connell becoming the youngest two-time Oscar winners.\n",
+ "- **Top winners:** *Oppenheimer* won seven awards, including Best Picture and Best Director (Christopher Nolan). *Poor Things* won four, and *The Zone of Interest* won two. *Oppenheimer* also led in nominations with 13, ahead of *Poor Things* (11).\n",
+ "- **Acting:** Cillian Murphy (Best Actor, *Oppenheimer*), Emma Stone (Best Actress, *Poor Things*), Robert Downey Jr. (Best Supporting Actor, *Oppenheimer*), and Da'Vine Joy Randolph (Best Supporting Actress, *The Holdovers*).\n",
+ "- **Other notable wins:** Billie Eilish and Finneas O'Connell won Best Original Song for \"What Was I Made For?\" from *Barbie*, and *The Zone of Interest* won Best International Feature Film. *Godzilla Minus One* won Best Visual Effects.\n",
+ "- **Records and firsts:** Martin Scorsese became the oldest Best Director nominee, and three Best Picture nominees were directed by women.\n",
+ "- **Ceremony details:** The show started an hour earlier than usual. Presenters and performers included Ryan Gosling performing \"I'm Just Ken.\" The \"In Memoriam\" segment featured Andrea Bocelli.\n",
+ "- **Controversy:** Jonathan Glazer's acceptance speech about the Israel–Gaza conflict drew praise and criticism, and led to open letters from both supporters and critics.\n",
+ "- **Reception:** The telecast drew about 19.49 million U.S. viewers, a 4% increase over the previous year. It later won four Primetime Emmys.\n",
"\n",
- "The ceremony featured musical performances, tributes to past winners, and a touching \"In Memoriam\" segment. However, it also faced some criticism, such as the distracting and hard-to-follow \"In Memoriam\" presentation and political controversy around a director's comments about the Israel-Gaza conflict.\n"
+ "The page also covers the Governors Awards (held January 9, 2024), the Academy's new Best Picture diversity standards, and box office performance of the nominees.\n"
]
}
],
"source": [
- "response = client.messages.create(model=MODEL_NAME, max_tokens=1024, messages=messages)\n",
+ "response = client.messages.create(model=MODEL_NAME, max_tokens=2048, messages=messages)\n",
"\n",
- "summary = response.content[0].text\n",
+ "# Read the text block by type: the response may start with a thinking block\n",
+ "summary = \"\".join(block.text for block in response.content if block.type == \"text\")\n",
"print(summary)"
]
}
@@ -127,7 +153,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.12"
+ "version": "3.12.3"
}
},
"nbformat": 4,
diff --git a/content/github/claude-cookbooks/misc/sampling_past_max_tokens.ipynb b/content/github/claude-cookbooks/misc/sampling_past_max_tokens.ipynb
index e5d2526817..a04b38044a 100644
--- a/content/github/claude-cookbooks/misc/sampling_past_max_tokens.ipynb
+++ b/content/github/claude-cookbooks/misc/sampling_past_max_tokens.ipynb
@@ -11,7 +11,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "> **Model note:** this notebook uses `claude-haiku-4-5` because assistant-message prefill (the continuation technique shown below) is only accepted on Claude Haiku 4.5 among current models; Claude Opus 5.5, Claude Sonnet 5.5, and Claude Fable 5.1 return a 400 for it. Those models also accept much larger `max_tokens` values (up to 128K output tokens; see the [models overview](https://platform.claude.com/docs/en/about-claude/models/overview)), so a single request usually suffices. If a response is still cut off on those models, continue with a new user turn such as \"Continue exactly where you left off.\" rather than an assistant prefill."
+ "> **Model note:** this notebook uses `claude-haiku-4-5`, a legacy model, because assistant-message prefill (the continuation technique shown below) is only accepted on Claude Haiku 4.5. All current models (Claude Opus 5.5, Claude Sonnet 5.5, Claude Fable 5.1, and Claude Haiku 5.5) return a 400 for a request that ends with an assistant message. Current models also accept much larger `max_tokens` values (up to 128K output tokens; see the [models overview](https://platform.claude.com/docs/en/about-claude/models/overview)), so a single request usually suffices. If a response is still cut off on a current model, continue with a new user turn such as \"Continue exactly where you left off.\" rather than an assistant prefill."
]
},
{
@@ -68,7 +68,8 @@
"\n",
"# Reads ANTHROPIC_API_KEY from the environment\n",
"client = anthropic.Anthropic()\n",
- "# See the model note at the top: the prefill continuation below is only accepted on Claude Haiku 4.5.\n",
+ "# See the model note at the top: the prefill continuation below is only accepted on the\n",
+ "# legacy Claude Haiku 4.5; current models, including Claude Haiku 5.5, return a 400 for it.\n",
"MODEL_NAME = \"claude-haiku-4-5\"\n",
"\n",
"message = client.messages.create(\n",
diff --git a/content/github/claude-cookbooks/multimodal/using_sub_agents.ipynb b/content/github/claude-cookbooks/multimodal/using_sub_agents.ipynb
index 2feeb0939b..c1b58a9646 100644
--- a/content/github/claude-cookbooks/multimodal/using_sub_agents.ipynb
+++ b/content/github/claude-cookbooks/multimodal/using_sub_agents.ipynb
@@ -6,7 +6,7 @@
"source": [
"# Using Haiku as a sub-agent\n",
"\n",
- "In this recipe, we'll demonstrate how to analyze Apple's 2023 financial earnings reports using Claude Haiku 4.5 sub-agent models to extract relevant information from earnings release PDFs. We'll then use Claude Opus 5.5 to generate a response to our question and create a graph using matplotlib to accompany its response."
+ "In this recipe, we'll demonstrate how to analyze Apple's 2023 financial earnings reports using Claude Haiku 5.5 sub-agent models to extract relevant information from earnings release PDFs. We'll then use Claude Opus 5.5 to generate a response to our question and create a graph using matplotlib to accompany its response."
]
},
{
@@ -45,7 +45,7 @@
"\n",
"# Set up the Claude API client\n",
"client = Anthropic()\n",
- "MODEL_NAME = \"claude-haiku-4-5\""
+ "MODEL_NAME = \"claude-haiku-5-5\""
]
},
{
@@ -235,7 +235,7 @@
" }\n",
" ]\n",
"\n",
- " response = client.messages.create(model=\"claude-haiku-4-5\", max_tokens=2048, messages=messages)\n",
+ " response = client.messages.create(model=MODEL_NAME, max_tokens=2048, messages=messages)\n",
"\n",
" return \"\".join(block.text for block in response.content if block.type == \"text\"), pdf_path\n",
"\n",
diff --git a/content/github/claude-cookbooks/third_party/ElevenLabs/low_latency_stt_claude_tts.ipynb b/content/github/claude-cookbooks/third_party/ElevenLabs/low_latency_stt_claude_tts.ipynb
index f0d859da3d..c89f687328 100644
--- a/content/github/claude-cookbooks/third_party/ElevenLabs/low_latency_stt_claude_tts.ipynb
+++ b/content/github/claude-cookbooks/third_party/ElevenLabs/low_latency_stt_claude_tts.ipynb
@@ -297,7 +297,7 @@
"source": [
"## Get a Response from Claude\n",
"\n",
- "Send the transcribed text to Claude and measure the response time. We're using `claude-haiku-4-5` for fast, high-quality responses:"
+ "Send the transcribed text to Claude and measure the response time. We're using `claude-haiku-5-5` with `effort: \"low\"` for fast, high-quality responses:"
]
},
{
@@ -320,16 +320,16 @@
"start_time = time.time()\n",
"\n",
"message = anthropic_client.messages.create(\n",
- " model=\"claude-haiku-4-5\",\n",
+ " model=\"claude-haiku-5-5\",\n",
" max_tokens=1000,\n",
- " temperature=0,\n",
+ " output_config={\"effort\": \"low\"},\n",
" messages=[{\"role\": \"user\", \"content\": transcription.text}],\n",
")\n",
"\n",
"end_time = time.time()\n",
"non_streaming_response_time = end_time - start_time\n",
"\n",
- "print(message.content[0].text)\n",
+ "print(\"\".join(b.text for b in message.content if b.type == \"text\"))\n",
"print(f\"\\nResponse time: {non_streaming_response_time:.2f} seconds\")"
]
},
@@ -366,9 +366,9 @@
"claude_full_response = \"\"\n",
"\n",
"with anthropic_client.messages.stream(\n",
- " model=\"claude-haiku-4-5\",\n",
+ " model=\"claude-haiku-5-5\",\n",
" max_tokens=1000,\n",
- " temperature=0,\n",
+ " output_config={\"effort\": \"low\"},\n",
" messages=[{\"role\": \"user\", \"content\": transcription.text}],\n",
") as stream:\n",
" for text in stream.text_stream:\n",
@@ -504,9 +504,9 @@
"first_audio_time = None\n",
"\n",
"with anthropic_client.messages.stream(\n",
- " model=\"claude-haiku-4-5\",\n",
+ " model=\"claude-haiku-5-5\",\n",
" max_tokens=1000,\n",
- " temperature=0,\n",
+ " output_config={\"effort\": \"low\"},\n",
" messages=[{\"role\": \"user\", \"content\": transcription.text}],\n",
") as stream:\n",
" for text in stream.text_stream:\n",
diff --git a/content/github/claude-cookbooks/third_party/Pinecone/rag_using_pinecone.ipynb b/content/github/claude-cookbooks/third_party/Pinecone/rag_using_pinecone.ipynb
index 3d74b03755..ed36802bf4 100644
--- a/content/github/claude-cookbooks/third_party/Pinecone/rag_using_pinecone.ipynb
+++ b/content/github/claude-cookbooks/third_party/Pinecone/rag_using_pinecone.ipynb
@@ -21,7 +21,7 @@
"metadata": {},
"source": [
"## Setup\n",
- "First, let's install the necessary libraries and set the API keys we will need to use in this notebook. We will need to get a [Claude API key](https://docs.claude.com/claude/reference/getting-started-with-the-api), a free [Pinecone API key](https://docs.pinecone.io/docs/quickstart), and a free [Voyage AI API key](https://docs.voyageai.com/install/). "
+ "First, let's install the necessary libraries and set the API keys we will need to use in this notebook. We will need to get a [Claude API key](https://docs.claude.com/en/api/overview), a free [Pinecone API key](https://docs.pinecone.io/docs/quickstart), and a free [Voyage AI API key](https://docs.voyageai.com/install/). "
]
},
{
@@ -87,7 +87,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "Next, we set up our index specification, which allows us to define the cloud provider and region where we want to deploy our index. You can find a list of all available providers and regions [here](https://www.pinecone.io/docs/data-types/metadata/).\n"
+ "Next, we set up our index specification, which allows us to define the cloud provider and region where we want to deploy our index. You can find a list of all available providers and regions [here](https://docs.pinecone.io/guides/index-data/indexing-overview).\n"
]
},
{
@@ -156,7 +156,7 @@
"## Embeddings\n",
"To get started with Voyage's embeddings, go [here](https://www.voyageai.com) to get an API key.\n",
"\n",
- "Now let's set up our Voyage client and demonstrate how to create an embedding using the `embed` method. To learn more about using Voyage embeddings with Claude, see [this notebook](https://github.com/anthropics/anthropic-cookbook/blob/main/third_party/VoyageAI/how_to_create_embeddings.md)."
+ "Now let's set up our Voyage client and demonstrate how to create an embedding using the `embed` method. To learn more about using Voyage embeddings with Claude, see [this notebook](https://github.com/anthropics/claude-cookbooks/blob/main/third_party/VoyageAI/how_to_create_embeddings.md)."
]
},
{
@@ -375,15 +375,16 @@
"import anthropic\n",
"\n",
"client = anthropic.Anthropic(api_key=ANTHROPIC_API_KEY)\n",
+ "MODEL_NAME = \"claude-haiku-5-5\"\n",
"\n",
"\n",
- "def get_completion(prompt):\n",
- " completion = client.completions.create(\n",
- " model=\"claude-2.1\",\n",
- " prompt=prompt,\n",
- " max_tokens_to_sample=1024,\n",
+ "def get_completion(messages):\n",
+ " response = client.messages.create(\n",
+ " model=MODEL_NAME,\n",
+ " max_tokens=1024,\n",
+ " messages=messages,\n",
" )\n",
- " return completion.completion"
+ " return \"\".join(b.text for b in response.content if b.type == \"text\")"
]
},
{
@@ -392,12 +393,13 @@
"metadata": {},
"outputs": [],
"source": [
- "def create_keyword_prompt(question):\n",
- " return f\"\"\"\\n\\nHuman: Given a question, generate a list of 5 very diverse search keywords that can be used to search for products on Amazon.\n",
+ "def create_keyword_messages(question):\n",
+ " user_content = f\"\"\"Given a question, generate a list of 5 very diverse search keywords that can be used to search for products on Amazon.\n",
"\n",
"The question is: {question}\n",
"\n",
- "Output your keywords as a JSON that has one property \"keywords\" that is a list of strings. Only output valid JSON.\\n\\nAssistant:{{\"\"\""
+ "Output your keywords as a JSON object that has one property \"keywords\" that is a list of strings. Wrap the JSON in tags and output nothing else.\"\"\"\n",
+ " return [{\"role\": \"user\", \"content\": user_content}]"
]
},
{
@@ -405,7 +407,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "With our Anthropic client setup and our prompt created, we can now begin to generate keywords from the question. We will output the keywords in a JSON object so we can easily parse them from Claude's output."
+ "With our Anthropic client set up and our prompt created, we can now generate keywords from the question. The prompt asks Claude to wrap the JSON in `` tags so we can extract it reliably."
]
},
{
@@ -414,7 +416,10 @@
"metadata": {},
"outputs": [],
"source": [
- "keyword_json = \"{\" + get_completion(create_keyword_prompt(USER_QUESTION))\n",
+ "import re\n",
+ "\n",
+ "raw = get_completion(create_keyword_messages(USER_QUESTION))\n",
+ "keyword_json = re.search(r\"(.*?)\", raw, re.DOTALL).group(1).strip()\n",
"print(keyword_json)"
]
},
@@ -470,7 +475,7 @@
},
{
"cell_type": "code",
- "execution_count": 47,
+ "execution_count": null,
"metadata": {},
"outputs": [],
"source": [
@@ -486,8 +491,11 @@
" return f\"\\n\\n{result}\\n\"\n",
"\n",
"\n",
- "def create_answer_prompt(results_list, question):\n",
- " return f\"\"\"\\n\\nHuman: {format_results(results_list)} Using the search results provided within the tags, please answer the following question {question}. Do not reference the search results in your answer.\\n\\nAssistant:\"\"\""
+ "def create_answer_messages(results_list, question):\n",
+ " user_content = f\"\"\"{format_results(results_list)}\n",
+ "\n",
+ "Using the search results provided within the tags, please answer the following question {question}. Do not reference the search results in your answer.\"\"\"\n",
+ " return [{\"role\": \"user\", \"content\": user_content}]"
]
},
{
@@ -500,19 +508,11 @@
},
{
"cell_type": "code",
- "execution_count": 50,
+ "execution_count": null,
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- " To get your daughter more interested in science, I would recommend getting her an age-appropriate science kit or set that allows for hands-on exploration and experimentation. For example, for a younger child you could try a beginner chemistry set, magnet set, or crystal growing kit. For an older child, look for kits that tackle more advanced scientific principles like physics, engineering, robotics, etc. The key is choosing something that sparks her natural curiosity and lets her actively investigate concepts through activities, observations, and discovery. Supplement the kits with science books, museum visits, documentaries, and conversations about science she encounters in everyday life. Making science fun and engaging is crucial for building her interest.\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
- "answer = get_completion(create_answer_prompt(results_list, USER_QUESTION))\n",
+ "answer = get_completion(create_answer_messages(results_list, USER_QUESTION))\n",
"print(answer)"
]
}
diff --git a/content/github/claude-cookbooks/third_party/WolframAlpha/using_llm_api.ipynb b/content/github/claude-cookbooks/third_party/WolframAlpha/using_llm_api.ipynb
index 6791722f75..1cbabd274a 100644
--- a/content/github/claude-cookbooks/third_party/WolframAlpha/using_llm_api.ipynb
+++ b/content/github/claude-cookbooks/third_party/WolframAlpha/using_llm_api.ipynb
@@ -32,7 +32,7 @@
"\n",
"# Replace 'YOUR_APP_ID' with your actual Wolfram Alpha AppID\n",
"WOLFRAM_APP_ID = \"YOUR_APP_ID\"\n",
- "MODEL_NAME = \"claude-haiku-4-5\""
+ "MODEL_NAME = \"claude-haiku-5-5\""
]
},
{
@@ -48,7 +48,7 @@
"execution_count": null,
"metadata": {},
"outputs": [],
- "source": "import urllib.parse\n\nimport requests\n\n\ndef wolfram_alpha_query(query):\n # URL-encode the query\n encoded_query = urllib.parse.quote(query)\n\n # Make a request to the Wolfram Alpha LLM API\n url = (\n f\"https://www.wolframalpha.com/api/v1/llm-api?input={encoded_query}&appid={WOLFRAM_APP_ID}\"\n )\n response = requests.get(url, timeout=30)\n\n if response.status_code == 200:\n return response.text\n else:\n return f\"Error: {response.status_code}: {response.text}\"\n\n\ntools = [\n {\n \"name\": \"wolfram_alpha\",\n \"description\": \"A tool that allows querying the Wolfram Alpha knowledge base. Useful for mathematical calculations, scientific data, and general knowledge questions.\",\n \"input_schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"search_query\": {\n \"type\": \"string\",\n \"description\": \"The query to send to the Wolfram Alpha API.\",\n }\n },\n \"required\": [\"query\"],\n },\n }\n]"
+ "source": "import urllib.parse\n\nimport requests\n\n\ndef wolfram_alpha_query(query):\n # URL-encode the query\n encoded_query = urllib.parse.quote(query)\n\n # Make a request to the Wolfram Alpha LLM API\n url = (\n f\"https://www.wolframalpha.com/api/v1/llm-api?input={encoded_query}&appid={WOLFRAM_APP_ID}\"\n )\n response = requests.get(url, timeout=30)\n\n if response.status_code == 200:\n return response.text\n else:\n return f\"Error: {response.status_code}: {response.text}\"\n\n\ntools = [\n {\n \"name\": \"wolfram_alpha\",\n \"description\": \"A tool that allows querying the Wolfram Alpha knowledge base. Useful for mathematical calculations, scientific data, and general knowledge questions.\",\n \"input_schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"search_query\": {\n \"type\": \"string\",\n \"description\": \"The query to send to the Wolfram Alpha API.\",\n }\n },\n \"required\": [\"search_query\"],\n },\n }\n]"
},
{
"cell_type": "markdown",
@@ -82,7 +82,7 @@
" print(f\"\\n{'=' * 50}\\nUser Message: {user_message}\\n{'=' * 50}\")\n",
" prompt = f\"\"\"Here is a question: {user_message}. Please use the Wolfram Alpha tool to answer it. Do not reflect on the quality of the returned search results in your response.\"\"\"\n",
"\n",
- " message = client.beta.tools.messages.create(\n",
+ " message = client.messages.create(\n",
" model=MODEL_NAME,\n",
" max_tokens=4096,\n",
" tools=tools,\n",
@@ -107,7 +107,7 @@
" print(\"\\nTool Result:\")\n",
" print(str(json.dumps(tool_result, indent=2)))\n",
"\n",
- " response = client.beta.tools.messages.create(\n",
+ " response = client.messages.create(\n",
" model=MODEL_NAME,\n",
" max_tokens=2000,\n",
" tools=tools,\n",
@@ -135,7 +135,7 @@
"\n",
" final_response = None\n",
" for block in response.content:\n",
- " if hasattr(block, \"text\"):\n",
+ " if block.type == \"text\":\n",
" final_response = block.text\n",
" break\n",
"\n",
diff --git a/content/github/claude-cookbooks/tool_use/context_engineering/context_engineering_tools.ipynb b/content/github/claude-cookbooks/tool_use/context_engineering/context_engineering_tools.ipynb
index efcb782f7b..35fbfe0500 100644
--- a/content/github/claude-cookbooks/tool_use/context_engineering/context_engineering_tools.ipynb
+++ b/content/github/claude-cookbooks/tool_use/context_engineering/context_engineering_tools.ipynb
@@ -77,7 +77,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "anthropic SDK 0.84.0, model claude-sonnet-4-6\n"
+ "anthropic SDK 0.109.0, model claude-sonnet-5-5\n"
]
}
],
@@ -2868,8 +2868,16 @@
"name": "python3"
},
"language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
"name": "python",
- "version": "3.11"
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.12.3"
}
},
"nbformat": 4,
diff --git a/content/github/claude-cookbooks/tool_use/extracting_structured_json.ipynb b/content/github/claude-cookbooks/tool_use/extracting_structured_json.ipynb
index 8f4bec58f2..caaabc7939 100644
--- a/content/github/claude-cookbooks/tool_use/extracting_structured_json.ipynb
+++ b/content/github/claude-cookbooks/tool_use/extracting_structured_json.ipynb
@@ -31,7 +31,7 @@
},
{
"cell_type": "code",
- "execution_count": 54,
+ "execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
@@ -42,7 +42,7 @@
"from bs4 import BeautifulSoup\n",
"\n",
"client = Anthropic()\n",
- "MODEL_NAME = \"claude-haiku-4-5\""
+ "MODEL_NAME = \"claude-haiku-5-5\""
]
},
{
@@ -56,10 +56,94 @@
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 2,
"metadata": {},
- "outputs": [],
- "source": "tools = [\n {\n \"name\": \"print_summary\",\n \"description\": \"Prints a summary of the article.\",\n \"input_schema\": {\n \"type\": \"object\",\n \"properties\": {\n \"author\": {\"type\": \"string\", \"description\": \"Name of the article author\"},\n \"topics\": {\n \"type\": \"array\",\n \"items\": {\"type\": \"string\"},\n \"description\": 'Array of topics, e.g. [\"tech\", \"politics\"]. Should be as specific as possible, and can overlap.',\n },\n \"summary\": {\n \"type\": \"string\",\n \"description\": \"Summary of the article. One or two paragraphs max.\",\n },\n \"coherence\": {\n \"type\": \"integer\",\n \"description\": \"Coherence of the article's key points, 0-100 (inclusive)\",\n },\n \"persuasion\": {\n \"type\": \"number\",\n \"description\": \"Article's persuasion score, 0.0-1.0 (inclusive)\",\n },\n },\n \"required\": [\"author\", \"topics\", \"summary\", \"coherence\", \"persuasion\", \"counterpoint\"],\n },\n }\n]\n\nurl = \"https://www.anthropic.com/news/third-party-testing\"\nresponse = requests.get(url, timeout=30)\nsoup = BeautifulSoup(response.text, \"html.parser\")\narticle = \" \".join([p.text for p in soup.find_all(\"p\")])\n\nquery = f\"\"\"\n\n{article}\n\n\nUse the `print_summary` tool.\n\"\"\"\n\nresponse = client.messages.create(\n model=MODEL_NAME, max_tokens=4096, tools=tools, messages=[{\"role\": \"user\", \"content\": query}]\n)\njson_summary = None\nfor content in response.content:\n if content.type == \"tool_use\" and content.name == \"print_summary\":\n json_summary = content.input\n break\n\nif json_summary:\n print(\"JSON Summary:\")\n print(json.dumps(json_summary, indent=2))\nelse:\n print(\"No JSON summary found in the response.\")"
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "JSON Summary:\n",
+ "{\n",
+ " \"author\": \"Anthropic\",\n",
+ " \"topics\": [\n",
+ " \"AI policy\",\n",
+ " \"AI safety\",\n",
+ " \"third-party testing\",\n",
+ " \"AI regulation\",\n",
+ " \"national security\",\n",
+ " \"regulatory capture\",\n",
+ " \"open-weight models\",\n",
+ " \"AI evaluation\"\n",
+ " ],\n",
+ " \"summary\": \"Anthropic argues that the AI sector needs an effective third-party testing regime for frontier AI systems, and that this regime should be developed through collaboration among industry, government, and academia. The company says such testing is needed to address issues like election integrity, harmful discrimination, and national security misuse, and that more capable future systems will require more expansive oversight. Anthropic expects that some form of third-party testing will eventually be a legal requirement for widely deploying AI models. It favors prototyping testing regimes now, since the standards, testers, and market structure are not yet clear. The post notes that frontier models are general-purpose \\\"everything machines\\\" whose downstream behavior inherits their capabilities and weaknesses, so existing sector-specific rules fit poorly. It cites precedents in food, medicine, automobiles, and aerospace, and proposes that national-security-relevant capabilities, such as meaningful uplift for bioweapons or complex cyberattacks, be tested first, with possible responses including removing capabilities, gating them behind know-your-customer checks, or notifying government agencies.\\n\\nThe post also describes Anthropic's Responsible Scaling Policy as a self-governance step, but argues that self-governance by single companies is insufficient and that testing must be broadly trusted and apply to all frontier developers. It addresses open-weight models and regulatory capture, acknowledging these as contested issues, and advocates a \\\"minimal viable policy\\\" because regulations tend to be hard to remove once passed. Specific policy asks include more government funding for AI evaluation, public-sector research infrastructure, tests for national-security capabilities, and scenario planning for advanced systems. The post ends with updates on Anthropic's testing collaborations (including METR and talks with Hugging Face), election safeguards, and a Singapore office, some of which are only loosely connected to the main argument.\",\n",
+ " \"coherence\": 70,\n",
+ " \"persuasion\": 0.7,\n",
+ " \"counterpoint\": \"The author is a frontier AI developer advocating for a regime that could raise compliance costs and favor well-resourced incumbents, which the post itself only partly addresses. Its proposals rely on testing methods that may not accurately measure safety, and the post offers little evidence that the proposed tests work. Open-weight advocates and smaller developers would likely argue that mandatory testing and licensing would entrench large players and limit open research. The post's list of required ingredients and responsible testers is also left incomplete, and its closing updates on elections and a Singapore office are unrelated to the core policy argument.\"\n",
+ "}\n"
+ ]
+ }
+ ],
+ "source": [
+ "tools = [\n",
+ " {\n",
+ " \"name\": \"print_summary\",\n",
+ " \"description\": \"Prints a summary of the article.\",\n",
+ " \"input_schema\": {\n",
+ " \"type\": \"object\",\n",
+ " \"properties\": {\n",
+ " \"author\": {\"type\": \"string\", \"description\": \"Name of the article author\"},\n",
+ " \"topics\": {\n",
+ " \"type\": \"array\",\n",
+ " \"items\": {\"type\": \"string\"},\n",
+ " \"description\": 'Array of topics, e.g. [\"tech\", \"politics\"]. Should be as specific as possible, and can overlap.',\n",
+ " },\n",
+ " \"summary\": {\n",
+ " \"type\": \"string\",\n",
+ " \"description\": \"Summary of the article. One or two paragraphs max.\",\n",
+ " },\n",
+ " \"coherence\": {\n",
+ " \"type\": \"integer\",\n",
+ " \"description\": \"Coherence of the article's key points, 0-100 (inclusive)\",\n",
+ " },\n",
+ " \"persuasion\": {\n",
+ " \"type\": \"number\",\n",
+ " \"description\": \"Article's persuasion score, 0.0-1.0 (inclusive)\",\n",
+ " },\n",
+ " },\n",
+ " \"required\": [\"author\", \"topics\", \"summary\", \"coherence\", \"persuasion\", \"counterpoint\"],\n",
+ " },\n",
+ " }\n",
+ "]\n",
+ "\n",
+ "url = \"https://www.anthropic.com/news/third-party-testing\"\n",
+ "response = requests.get(url, timeout=30)\n",
+ "soup = BeautifulSoup(response.text, \"html.parser\")\n",
+ "article = \" \".join([p.text for p in soup.find_all(\"p\")])\n",
+ "\n",
+ "query = f\"\"\"\n",
+ "\n",
+ "{article}\n",
+ "\n",
+ "\n",
+ "Use the `print_summary` tool.\n",
+ "\"\"\"\n",
+ "\n",
+ "response = client.messages.create(\n",
+ " model=MODEL_NAME, max_tokens=4096, tools=tools, messages=[{\"role\": \"user\", \"content\": query}]\n",
+ ")\n",
+ "json_summary = None\n",
+ "for content in response.content:\n",
+ " if content.type == \"tool_use\" and content.name == \"print_summary\":\n",
+ " json_summary = content.input\n",
+ " break\n",
+ "\n",
+ "if json_summary:\n",
+ " print(\"JSON Summary:\")\n",
+ " print(json.dumps(json_summary, indent=2))\n",
+ "else:\n",
+ " print(\"No JSON summary found in the response.\")"
+ ]
},
{
"cell_type": "markdown",
@@ -71,7 +155,7 @@
},
{
"cell_type": "code",
- "execution_count": 63,
+ "execution_count": 3,
"metadata": {},
"outputs": [
{
@@ -152,7 +236,7 @@
},
{
"cell_type": "code",
- "execution_count": 64,
+ "execution_count": 4,
"metadata": {},
"outputs": [
{
@@ -161,9 +245,9 @@
"text": [
"Sentiment Analysis (JSON):\n",
"{\n",
- " \"negative_score\": 0.6,\n",
- " \"neutral_score\": 0.3,\n",
- " \"positive_score\": 0.1\n",
+ " \"positive_score\": 0.1,\n",
+ " \"negative_score\": 0.7,\n",
+ " \"neutral_score\": 0.2\n",
"}\n"
]
}
@@ -231,7 +315,7 @@
},
{
"cell_type": "code",
- "execution_count": 66,
+ "execution_count": 5,
"metadata": {},
"outputs": [
{
@@ -242,24 +326,24 @@
"{\n",
" \"categories\": [\n",
" {\n",
- " \"name\": \"Politics\",\n",
- " \"score\": 0.1\n",
+ " \"name\": \"Technology\",\n",
+ " \"score\": 0.95\n",
" },\n",
" {\n",
- " \"name\": \"Sports\",\n",
- " \"score\": 0.1\n",
+ " \"name\": \"Business\",\n",
+ " \"score\": 0.3\n",
" },\n",
" {\n",
- " \"name\": \"Technology\",\n",
- " \"score\": 0.7\n",
+ " \"name\": \"Politics\",\n",
+ " \"score\": 0.02\n",
" },\n",
" {\n",
- " \"name\": \"Entertainment\",\n",
- " \"score\": 0.1\n",
+ " \"name\": \"Sports\",\n",
+ " \"score\": 0.01\n",
" },\n",
" {\n",
- " \"name\": \"Business\",\n",
- " \"score\": 0.5\n",
+ " \"name\": \"Entertainment\",\n",
+ " \"score\": 0.02\n",
" }\n",
" ]\n",
"}\n"
@@ -332,7 +416,7 @@
},
{
"cell_type": "code",
- "execution_count": 5,
+ "execution_count": 6,
"metadata": {},
"outputs": [
{
@@ -342,9 +426,10 @@
"Characteristics (JSON):\n",
"{\n",
" \"height\": \"tall\",\n",
+ " \"gender\": \"man\",\n",
" \"facial_hair\": \"beard\",\n",
- " \"facial_features\": \"scar on left cheek\",\n",
- " \"voice\": \"deep voice\",\n",
+ " \"distinguishing_marks\": \"scar on left cheek\",\n",
+ " \"voice\": \"deep\",\n",
" \"clothing\": \"black leather jacket\"\n",
"}\n"
]
@@ -385,7 +470,7 @@
"\n",
"if tool_output:\n",
" print(\"Characteristics (JSON):\")\n",
- " print(json.dumps(json_classification, indent=2))\n",
+ " print(json.dumps(tool_output, indent=2))\n",
"else:\n",
" print(\"Something went wrong.\")"
]
@@ -414,7 +499,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.11.8"
+ "version": "3.12.3"
}
},
"nbformat": 4,
diff --git a/content/github/claude-cookbooks/tool_use/memory_cookbook.ipynb b/content/github/claude-cookbooks/tool_use/memory_cookbook.ipynb
index 0a83c6d7f3..ced7bba799 100644
--- a/content/github/claude-cookbooks/tool_use/memory_cookbook.ipynb
+++ b/content/github/claude-cookbooks/tool_use/memory_cookbook.ipynb
@@ -75,7 +75,51 @@
{
"cell_type": "markdown",
"metadata": {},
- "source": "## 1. Introduction: Why Memory Matters {#introduction}\n\nThis cookbook demonstrates practical implementations of the context engineering patterns described in [Effective context engineering for AI agents](https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents). That post covers why context is a finite resource, how attention budgets work, and strategies for building effective agents—the techniques you'll see in action here.\n\n### The Problem\n\nLarge language models have finite context windows (1M tokens on current Opus and Sonnet models, 200K on Haiku 4.5). While this seems large, several challenges emerge:\n\n- **Context limits**: Long conversations or complex tasks can exceed available context\n- **Computational cost**: Processing large contexts is expensive - attention mechanisms scale quadratically\n- **Repeated patterns**: Similar tasks across conversations require re-explaining context every time\n- **Information loss**: When context fills up, earlier important information gets lost\n\n### The Solution\n\nCurrent Claude models support powerful context management capabilities:\n\n1. **Memory Tool** (`memory_20250818`): Enables cross-conversation learning\n - Claude can write down what it learns for future reference\n - File-based system under `/memories` directory\n - Client-side implementation gives you full control\n\n2. **Context Editing**: Automatically manages context with two strategies:\n - **Tool use clearing** (`clear_tool_uses_20250919`): Clears old tool results when context grows large\n - **Thinking management** (`clear_thinking_20251015`): Manages extended thinking blocks (requires thinking enabled)\n - Configurable triggers and retention policies\n\n### The Benefit\n\nBuild AI agents that **get better at your specific tasks over time**:\n\n- **Session 1**: Claude solves a problem, writes down the pattern\n- **Session 2**: Claude applies the learned pattern immediately (faster!)\n- **Long sessions**: Context editing keeps conversations manageable\n\nThink of it as giving Claude a notebook to take notes and refer back to - just like humans do.\n\n### What You'll Learn\n\nBy the end of this cookbook, you will be able to:\n- **Implement** the memory tool for cross-conversation learning\n- **Configure** context editing to manage long-running sessions\n- **Apply** best practices for memory security and organization"
+ "source": [
+ "## 1. Introduction: Why Memory Matters {#introduction}\n",
+ "\n",
+ "This cookbook demonstrates practical implementations of the context engineering patterns described in [Effective context engineering for AI agents](https://www.anthropic.com/engineering/effective-context-engineering-for-ai-agents). That post covers why context is a finite resource, how attention budgets work, and strategies for building effective agents—the techniques you'll see in action here.\n",
+ "\n",
+ "### The Problem\n",
+ "\n",
+ "Large language models have finite context windows (1M tokens on all current Claude models). While this seems large, several challenges emerge:\n",
+ "\n",
+ "- **Context limits**: Long conversations or complex tasks can exceed available context\n",
+ "- **Computational cost**: Processing large contexts is expensive - attention mechanisms scale quadratically\n",
+ "- **Repeated patterns**: Similar tasks across conversations require re-explaining context every time\n",
+ "- **Information loss**: When context fills up, earlier important information gets lost\n",
+ "\n",
+ "### The Solution\n",
+ "\n",
+ "Current Claude models support powerful context management capabilities:\n",
+ "\n",
+ "1. **Memory Tool** (`memory_20250818`): Enables cross-conversation learning\n",
+ " - Claude can write down what it learns for future reference\n",
+ " - File-based system under `/memories` directory\n",
+ " - Client-side implementation gives you full control\n",
+ "\n",
+ "2. **Context Editing**: Automatically manages context with two strategies:\n",
+ " - **Tool use clearing** (`clear_tool_uses_20250919`): Clears old tool results when context grows large\n",
+ " - **Thinking management** (`clear_thinking_20251015`): Manages extended thinking blocks (requires thinking enabled)\n",
+ " - Configurable triggers and retention policies\n",
+ "\n",
+ "### The Benefit\n",
+ "\n",
+ "Build AI agents that **get better at your specific tasks over time**:\n",
+ "\n",
+ "- **Session 1**: Claude solves a problem, writes down the pattern\n",
+ "- **Session 2**: Claude applies the learned pattern immediately (faster!)\n",
+ "- **Long sessions**: Context editing keeps conversations manageable\n",
+ "\n",
+ "Think of it as giving Claude a notebook to take notes and refer back to - just like humans do.\n",
+ "\n",
+ "### What You'll Learn\n",
+ "\n",
+ "By the end of this cookbook, you will be able to:\n",
+ "- **Implement** the memory tool for cross-conversation learning\n",
+ "- **Configure** context editing to manage long-running sessions\n",
+ "- **Apply** best practices for memory security and organization"
+ ]
},
{
"cell_type": "markdown",
@@ -87,7 +131,7 @@
"\n",
"### The Problem\n",
"\n",
- "Large language models have finite context windows (1M tokens on current Opus and Sonnet models, 200K on Haiku 4.5). While this seems large, several challenges emerge:\n",
+ "Large language models have finite context windows (1M tokens on all current Claude models). While this seems large, several challenges emerge:\n",
"\n",
"- **Context limits**: Long conversations or complex tasks can exceed available context\n",
"- **Computational cost**: Processing large contexts is expensive - attention mechanisms scale quadratically\n",
@@ -103,7 +147,7 @@
" - File-based system under `/memories` directory\n",
" - Client-side implementation gives you full control\n",
"\n",
- "**Supported Models**: Claude Opus 5.5 (`claude-opus-5-5`), Claude Sonnet 5.5 (`claude-sonnet-5-5`), and Claude Haiku 4.5 (`claude-haiku-4-5`)\n",
+ "**Supported Models**: Claude Opus 5.5 (`claude-opus-5-5`), Claude Sonnet 5.5 (`claude-sonnet-5-5`), and Claude Haiku 5.5 (`claude-haiku-5-5`)\n",
"\n",
"### The Benefit\n",
"\n",
@@ -119,7 +163,36 @@
{
"cell_type": "markdown",
"metadata": {},
- "source": "## 2. Use Cases {#use-cases}\n\nMemory and context management enable powerful new workflows:\n\n### 🔍 Code Review Assistant\n- Learns debugging patterns from past reviews\n- Recognizes similar bugs instantly in future sessions\n- Builds team-specific code quality knowledge\n- **Production ready**: Integrate with [claude-code-action](https://github.com/anthropics/claude-code-action) for GitHub PR reviews\n\n### 📚 Research Assistant\n- Accumulates knowledge on topics over multiple sessions\n- Connects insights across different research threads\n- Maintains bibliography and source tracking\n\n### 💬 Customer Support Bot\n- Learns user preferences and communication style\n- Remembers common issues and solutions\n- Builds product knowledge base from interactions\n\n### 📊 Data Analysis Helper\n- Remembers dataset patterns and anomalies\n- Stores analysis techniques that work well\n- Builds domain-specific insights over time\n\n**Supported Models**: Claude Opus 5.5 (`claude-opus-5-5`), Claude Sonnet 5.5 (`claude-sonnet-5-5`), and Claude Haiku 4.5 (`claude-haiku-4-5`)\n\n**This cookbook focuses on the Code Review Assistant** as it clearly demonstrates both memory (learning patterns) and context editing (handling long reviews)."
+ "source": [
+ "## 2. Use Cases {#use-cases}\n",
+ "\n",
+ "Memory and context management enable powerful new workflows:\n",
+ "\n",
+ "### 🔍 Code Review Assistant\n",
+ "- Learns debugging patterns from past reviews\n",
+ "- Recognizes similar bugs instantly in future sessions\n",
+ "- Builds team-specific code quality knowledge\n",
+ "- **Production ready**: Integrate with [claude-code-action](https://github.com/anthropics/claude-code-action) for GitHub PR reviews\n",
+ "\n",
+ "### 📚 Research Assistant\n",
+ "- Accumulates knowledge on topics over multiple sessions\n",
+ "- Connects insights across different research threads\n",
+ "- Maintains bibliography and source tracking\n",
+ "\n",
+ "### 💬 Customer Support Bot\n",
+ "- Learns user preferences and communication style\n",
+ "- Remembers common issues and solutions\n",
+ "- Builds product knowledge base from interactions\n",
+ "\n",
+ "### 📊 Data Analysis Helper\n",
+ "- Remembers dataset patterns and anomalies\n",
+ "- Stores analysis techniques that work well\n",
+ "- Builds domain-specific insights over time\n",
+ "\n",
+ "**Supported Models**: Claude Opus 5.5 (`claude-opus-5-5`), Claude Sonnet 5.5 (`claude-sonnet-5-5`), and Claude Haiku 5.5 (`claude-haiku-5-5`)\n",
+ "\n",
+ "**This cookbook focuses on the Code Review Assistant** as it clearly demonstrates both memory (learning patterns) and context editing (handling long reviews)."
+ ]
},
{
"cell_type": "markdown",
@@ -143,12 +216,6 @@
"cell_type": "code",
"execution_count": 1,
"metadata": {
- "execution": {
- "iopub.execute_input": "2025-11-15T17:11:26.527705Z",
- "iopub.status.busy": "2025-11-15T17:11:26.527494Z",
- "iopub.status.idle": "2025-11-15T17:11:30.063615Z",
- "shell.execute_reply": "2025-11-15T17:11:30.063106Z"
- },
"vscode": {
"languageId": "python"
}
@@ -188,7 +255,7 @@
"output_type": "stream",
"text": [
"✓ API key loaded\n",
- "✓ Using model: claude-sonnet-4-6\n"
+ "✓ Using model: claude-sonnet-5-5\n"
]
}
],
@@ -207,6 +274,7 @@
"if os.getenv(\"ANTHROPIC_MODEL\"):\n",
" MODEL = os.getenv(\"ANTHROPIC_MODEL\")\n",
"\n",
+ "API_KEY = os.getenv(\"ANTHROPIC_API_KEY\")\n",
"if not API_KEY:\n",
" raise ValueError(\"ANTHROPIC_API_KEY not found. Copy .env.example to .env and add your API key.\")\n",
"\n",
@@ -268,12 +336,6 @@
"cell_type": "code",
"execution_count": 3,
"metadata": {
- "execution": {
- "iopub.execute_input": "2025-11-15T17:11:30.331182Z",
- "iopub.status.busy": "2025-11-15T17:11:30.331084Z",
- "iopub.status.idle": "2025-11-15T17:12:09.831980Z",
- "shell.execute_reply": "2025-11-15T17:12:09.831417Z"
- },
"vscode": {
"languageId": "python"
}
@@ -554,9 +616,9 @@
"source": [
"# Import helper functions\n",
"from memory_demo.demo_helpers import (\n",
+ " print_context_management_info,\n",
" run_conversation_loop,\n",
" run_conversation_turn,\n",
- " print_context_management_info,\n",
")\n",
"from memory_tool import MemoryToolHandler\n",
"\n",
@@ -570,7 +632,7 @@
"print(\"✓ Memory cleared\\n\")\n",
"\n",
"# Load example code with a race condition bug\n",
- "with open(\"memory_demo/sample_code/web_scraper_v1.py\", \"r\") as f:\n",
+ "with open(\"memory_demo/sample_code/web_scraper_v1.py\") as f:\n",
" code_to_review = f.read()\n",
"\n",
"messages = [\n",
@@ -627,12 +689,6 @@
"cell_type": "code",
"execution_count": 4,
"metadata": {
- "execution": {
- "iopub.execute_input": "2025-11-15T17:12:09.834796Z",
- "iopub.status.busy": "2025-11-15T17:12:09.834455Z",
- "iopub.status.idle": "2025-11-15T17:12:49.692649Z",
- "shell.execute_reply": "2025-11-15T17:12:49.692286Z"
- },
"vscode": {
"languageId": "python"
}
@@ -937,7 +993,7 @@
"source": [
"# NEW conversation (empty messages)\n",
"# Load API client code with similar concurrency issue\n",
- "with open(\"memory_demo/sample_code/api_client_v1.py\", \"r\") as f:\n",
+ "with open(\"memory_demo/sample_code/api_client_v1.py\") as f:\n",
" code_to_review = f.read()\n",
"\n",
"messages = [\n",
@@ -1046,14 +1102,14 @@
" # Thinking management MUST come first when combining strategies\n",
" {\n",
" \"type\": \"clear_thinking_20251015\",\n",
- " \"keep\": {\"type\": \"thinking_turns\", \"value\": 1} # Keep only last turn's thinking\n",
+ " \"keep\": {\"type\": \"thinking_turns\", \"value\": 1}, # Keep only last turn's thinking\n",
" },\n",
" {\n",
" \"type\": \"clear_tool_uses_20250919\",\n",
" \"trigger\": {\"type\": \"input_tokens\", \"value\": 5000}, # Low threshold for demo\n",
" \"keep\": {\"type\": \"tool_uses\", \"value\": 2}, # Keep last 2 tool uses\n",
- " \"clear_at_least\": {\"type\": \"input_tokens\", \"value\": 2000}\n",
- " }\n",
+ " \"clear_at_least\": {\"type\": \"input_tokens\", \"value\": 2000},\n",
+ " },\n",
" ]\n",
"}\n",
"\n",
@@ -1082,13 +1138,15 @@
"messages = cleaned_messages\n",
"\n",
"# Review 1: Data processor (larger file)\n",
- "with open(\"memory_demo/sample_code/data_processor_v1.py\", \"r\") as f:\n",
+ "with open(\"memory_demo/sample_code/data_processor_v1.py\") as f:\n",
" data_processor_code = f.read()\n",
"\n",
- "messages.append({\n",
- " \"role\": \"user\",\n",
- " \"content\": f\"Review this data processor:\\n\\n```python\\n{data_processor_code}\\n```\"\n",
- "})\n",
+ "messages.append(\n",
+ " {\n",
+ " \"role\": \"user\",\n",
+ " \"content\": f\"Review this data processor:\\n\\n```python\\n{data_processor_code}\\n```\",\n",
+ " }\n",
+ ")\n",
"\n",
"print(\"📝 Review 1: Data processor\")\n",
"response = run_conversation_turn(\n",
@@ -1100,7 +1158,7 @@
" context_management=CONTEXT_MANAGEMENT,\n",
" thinking=THINKING,\n",
" max_tokens=4096,\n",
- " verbose=True\n",
+ " verbose=True,\n",
")\n",
"\n",
"# Add response to messages\n",
@@ -1113,13 +1171,12 @@
"print()\n",
"\n",
"# Review 2: SQL code\n",
- "with open(\"memory_demo/sample_code/sql_query_builder.py\", \"r\") as f:\n",
+ "with open(\"memory_demo/sample_code/sql_query_builder.py\") as f:\n",
" sql_code = f.read()\n",
"\n",
- "messages.append({\n",
- " \"role\": \"user\",\n",
- " \"content\": f\"Review this SQL query builder:\\n\\n```python\\n{sql_code}\\n```\"\n",
- "})\n",
+ "messages.append(\n",
+ " {\"role\": \"user\", \"content\": f\"Review this SQL query builder:\\n\\n```python\\n{sql_code}\\n```\"}\n",
+ ")\n",
"\n",
"print(\"📝 Review 2: SQL query builder\")\n",
"response = run_conversation_turn(\n",
@@ -1131,7 +1188,7 @@
" context_management=CONTEXT_MANAGEMENT,\n",
" thinking=THINKING,\n",
" max_tokens=4096,\n",
- " verbose=True\n",
+ " verbose=True,\n",
")\n",
"\n",
"messages.append({\"role\": \"assistant\", \"content\": response[1]})\n",
@@ -1143,13 +1200,12 @@
"print()\n",
"\n",
"# Review 3: Add one more review to ensure we trigger clearing\n",
- "with open(\"memory_demo/sample_code/web_scraper_v1.py\", \"r\") as f:\n",
+ "with open(\"memory_demo/sample_code/web_scraper_v1.py\") as f:\n",
" scraper_code = f.read()\n",
"\n",
- "messages.append({\n",
- " \"role\": \"user\",\n",
- " \"content\": f\"Quick check - any issues here?\\n\\n```python\\n{scraper_code}\\n```\"\n",
- "})\n",
+ "messages.append(\n",
+ " {\"role\": \"user\", \"content\": f\"Quick check - any issues here?\\n\\n```python\\n{scraper_code}\\n```\"}\n",
+ ")\n",
"\n",
"print(\"📝 Review 3: Web scraper (should trigger clearing)\")\n",
"response = run_conversation_turn(\n",
@@ -1161,7 +1217,7 @@
" context_management=CONTEXT_MANAGEMENT,\n",
" thinking=THINKING,\n",
" max_tokens=4096,\n",
- " verbose=True\n",
+ " verbose=True,\n",
")\n",
"\n",
"messages.append({\"role\": \"assistant\", \"content\": response[1]})\n",
@@ -1222,7 +1278,7 @@
"print(\"📂 Memory files in demo_memory/:\")\n",
"print()\n",
"\n",
- "for root, dirs, files in os.walk(\"./demo_memory\"):\n",
+ "for root, _dirs, files in os.walk(\"./demo_memory\"):\n",
" # Calculate relative path for display\n",
" level = root.replace(\"./demo_memory\", \"\").count(os.sep)\n",
" indent = \" \" * level\n",
@@ -1597,20 +1653,21 @@
],
"metadata": {
"kernelspec": {
- "display_name": "Coconut",
- "language": "coconut",
- "name": "coconut"
+ "display_name": "Python 3",
+ "language": "python",
+ "name": "python3"
},
"language_info": {
"codemirror_mode": {
- "name": "python",
+ "name": "ipython",
"version": 3
},
- "file_extension": ".coco",
- "mimetype": "text/x-python3",
- "name": "coconut",
- "pygments_lexer": "coconut",
- "version": "3.0.2"
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.12.3"
}
},
"nbformat": 4,
diff --git a/content/github/claude-cookbooks/tool_use/tool_choice.ipynb b/content/github/claude-cookbooks/tool_use/tool_choice.ipynb
index 95ef729e04..758f88b838 100644
--- a/content/github/claude-cookbooks/tool_use/tool_choice.ipynb
+++ b/content/github/claude-cookbooks/tool_use/tool_choice.ipynb
@@ -31,14 +31,14 @@
"from anthropic import Anthropic\n",
"\n",
"client = Anthropic()\n",
- "MODEL_NAME = \"claude-haiku-4-5\""
+ "MODEL_NAME = \"claude-haiku-5-5\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
- "> **Model note:** this notebook uses `claude-haiku-4-5` because forced `tool_choice` (`{\"type\": \"tool\"}` / `{\"type\": \"any\"}`) is only accepted on Claude Haiku 4.5 among current models. Claude Opus 5.5, Claude Sonnet 5.5, and Claude Fable 5.1 return a 400 for it; on those models use `tool_choice: {\"type\": \"auto\"}` with an explicit instruction naming the tool, add `\"strict\": true` to the tool definition, or use structured outputs (`output_config.format`)."
+ "> **Model note:** this notebook uses `claude-haiku-5-5` because forced `tool_choice` (`{\"type\": \"tool\"}` / `{\"type\": \"any\"}`) is accepted on Claude Haiku 5.5 but rejected with a 400 by Claude Opus 5.5, Claude Sonnet 5.5, and Claude Fable 5.1. On those models use `tool_choice: {\"type\": \"auto\"}` with an explicit instruction naming the tool, add `\"strict\": true` to the tool definition, or use structured outputs (`output_config.format`). Haiku 5.5 may return `thinking` blocks before the `tool_use` block, so read blocks by `type` rather than by position."
]
},
{
@@ -115,7 +115,7 @@
" system=system_prompt,\n",
" model=MODEL_NAME,\n",
" messages=messages,\n",
- " max_tokens=1000,\n",
+ " max_tokens=2048,\n",
" tool_choice={\"type\": \"auto\"},\n",
" tools=[web_search_tool],\n",
" )\n",
@@ -145,14 +145,9 @@
"output_type": "stream",
"text": [
"Claude did NOT call a tool\n",
- "Assistant: The sky is **blue** during the day. This blue color is caused by Rayleigh scattering, where shorter blue wavelengths of sunlight are scattered more effectively by nitrogen and oxygen molecules in the atmosphere than longer red wavelengths.\n",
+ "Assistant: The sky is usually blue during the day. This happens because of Rayleigh scattering: sunlight passes through the atmosphere, and shorter blue wavelengths scatter off air molecules more than longer red wavelengths do, so blue light reaches our eyes from all directions.\n",
"\n",
- "However, the sky can appear different colors depending on conditions:\n",
- "- **Red, orange, or pink** during sunrise and sunset due to the sun's light passing through more atmosphere\n",
- "- **Gray or white** on cloudy days when clouds block direct sunlight\n",
- "- **Dark blue or black** at night when there's no sunlight (though the night sky also contains stars and other celestial objects)\n",
- "\n",
- "So while \"blue\" is the classic answer for a clear daytime sky, the actual color varies based on time of day, weather, and atmospheric conditions.\n"
+ "The sky can look different under other conditions. At sunrise and sunset it often looks orange, pink, or red, because light travels through more atmosphere and the blue is scattered out. On cloudy days it can look gray or white, and at night it is dark.\n"
]
}
],
@@ -177,7 +172,7 @@
"output_type": "stream",
"text": [
"Claude wants to use a tool\n",
- "ToolUseBlock(id='toolu_01AsLwejRHxKSzZusy4VtYbw', caller=DirectCaller(type='direct'), input={'topic': 'most recent Miami Grand Prix winner 2026'}, name='web_search', type='tool_use')\n"
+ "ToolUseBlock(id='toolu_01SpdeYBZfEhEMHUgC45MLau', caller=DirectCaller(type='direct'), input={'topic': 'Miami Grand Prix 2026 race winner'}, name='web_search', type='tool_use')\n"
]
}
],
@@ -204,7 +199,7 @@
"output_type": "stream",
"text": [
"Claude did NOT call a tool\n",
- "Assistant: The Los Angeles Rams won Super Bowl LVI in 2022, defeating the Cincinnati Bengals 23-20 on February 13, 2022, at SoFi Stadium in Inglewood, California.\n"
+ "Assistant: The **Los Angeles Rams** won Super Bowl LVI in February 2022, beating the Cincinnati Bengals 23–20 at SoFi Stadium in Inglewood, California.\n"
]
}
],
@@ -223,7 +218,7 @@
"output_type": "stream",
"text": [
"Claude wants to use a tool\n",
- "ToolUseBlock(id='toolu_01615V2dnTTdPk8TsbhURk5d', caller=DirectCaller(type='direct'), input={'topic': 'most recent Super Bowl 2026 winner'}, name='web_search', type='tool_use')\n"
+ "ToolUseBlock(id='toolu_01538T8powgXWLgxc53avSnj', caller=DirectCaller(type='direct'), input={'topic': 'Super Bowl LX winner February 2026'}, name='web_search', type='tool_use')\n"
]
}
],
@@ -355,7 +350,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Message(id='msg_011CfdhjCpVa2tesx8oWXx3t', container=None, content=[TextBlock(citations=None, text=\"That's awesome! It sounds like you're really excited about what you cooked up! 🎉 \\n\\nI'd love to hear more about it! What did you make? What made it so incredible - was it a new recipe you tried, a special ingredient, or something else? Did you cook for yourself or share it with others?\", type='text')], model='claude-haiku-4-5-20251001', role='assistant', stop_details=None, stop_reason='end_turn', stop_sequence=None, type='message', usage=Usage(cache_creation=CacheCreation(ephemeral_1h_input_tokens=0, ephemeral_5m_input_tokens=0), cache_creation_input_tokens=0, cache_read_input_tokens=0, inference_geo='not_available', input_tokens=766, output_tokens=74, output_tokens_details=None, server_tool_use=None, service_tier='standard'), diagnostics=None)\n"
+ "Message(id='msg_011Cg4UE1eK9vKN67pFtQGAE', container=None, content=[ThinkingBlock(signature='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', thinking=\"The user says a sentence. They didn't ask for sentiment analysis explicitly. The tool prints sentiment scores of a given text, but the tool takes scores as input, not text. Odd tool: it takes positive/negative/neutral scores as parameters. I could compute the sentiment myself and call the tool. But is that appropriate? The user just made an exclamation. Perhaps they want a reply. I should respond warmly and ask what meal. Maybe don't call tools. Keep short.\", type='thinking'), TextBlock(citations=None, text=\"That sounds like a great cooking win! What did you make? I'd love to hear about it, whether it was a new recipe or something you improvised.\", type='text')], model='claude-haiku-5-5', role='assistant', stop_details=None, stop_reason='end_turn', stop_sequence=None, type='message', usage=Usage(cache_creation=CacheCreation(ephemeral_1h_input_tokens=0, ephemeral_5m_input_tokens=0), cache_creation_input_tokens=0, cache_read_input_tokens=0, inference_geo='global', input_tokens=641, output_tokens=204, output_tokens_details=OutputTokensDetails(thinking_tokens=159), server_tool_use=None, service_tier='standard', iterations=[{'input_tokens': 641, 'output_tokens': 204, 'cache_read_input_tokens': 0, 'cache_creation_input_tokens': 0, 'cache_creation': {'ephemeral_5m_input_tokens': 0, 'ephemeral_1h_input_tokens': 0}, 'type': 'message'}]), diagnostics=None)\n"
]
}
],
@@ -382,7 +377,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Message(id='msg_011CfdhjJUZXEKdg4iMFi58K', container=None, content=[TextBlock(citations=None, text='What a wonderful thing! Let me calculate that for you!', type='text'), ToolUseBlock(id='toolu_017GQKUsXCx6FigFjDRwqSHJ', caller=DirectCaller(type='direct'), input={'num1': 4, 'num2': 2}, name='calculator', type='tool_use')], model='claude-haiku-4-5-20251001', role='assistant', stop_details=None, stop_reason='tool_use', stop_sequence=None, type='message', usage=Usage(cache_creation=CacheCreation(ephemeral_1h_input_tokens=0, ephemeral_5m_input_tokens=0), cache_creation_input_tokens=0, cache_read_input_tokens=0, inference_geo='not_available', input_tokens=779, output_tokens=83, output_tokens_details=None, server_tool_use=None, service_tier='standard'), diagnostics=None)\n"
+ "Message(id='msg_011Cg4UE7w5FcmGvkmnTu5VZ', container=None, content=[ThinkingBlock(signature='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', thinking=\"The user asks a simple math question: 4 + 2 = 6. I can use calculator tool. Should I? It's simple; could just answer. The tool exists; using it is fine. I'll call calculator with 4 and 2.\", type='thinking'), ToolUseBlock(id='toolu_01DoLR6PzfydqVfjbS9iRgQ6', caller=DirectCaller(type='direct'), input={'num1': 4, 'num2': 2}, name='calculator', type='tool_use')], model='claude-haiku-5-5', role='assistant', stop_details=None, stop_reason='tool_use', stop_sequence=None, type='message', usage=Usage(cache_creation=CacheCreation(ephemeral_1h_input_tokens=0, ephemeral_5m_input_tokens=0), cache_creation_input_tokens=0, cache_read_input_tokens=0, inference_geo='global', input_tokens=652, output_tokens=144, output_tokens_details=OutputTokensDetails(thinking_tokens=73), server_tool_use=None, service_tier='standard', iterations=[{'input_tokens': 652, 'output_tokens': 144, 'cache_read_input_tokens': 0, 'cache_creation_input_tokens': 0, 'cache_creation': {'ephemeral_5m_input_tokens': 0, 'ephemeral_1h_input_tokens': 0}, 'type': 'message'}]), diagnostics=None)\n"
]
}
],
@@ -449,7 +444,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Message(id='msg_011CfdhjXVtYfE9vCYWCVHQu', container=None, content=[ToolUseBlock(id='toolu_01KKZ2sFuBq7wr2VjtneEibS', caller=DirectCaller(type='direct'), input={'positive_score': 0.95, 'negative_score': 0.02, 'neutral_score': 0.03}, name='print_sentiment_scores', type='tool_use')], model='claude-haiku-4-5-20251001', role='assistant', stop_details=None, stop_reason='tool_use', stop_sequence=None, type='message', usage=Usage(cache_creation=CacheCreation(ephemeral_1h_input_tokens=0, ephemeral_5m_input_tokens=0), cache_creation_input_tokens=0, cache_read_input_tokens=0, inference_geo='not_available', input_tokens=865, output_tokens=79, output_tokens_details=None, server_tool_use=None, service_tier='standard'), diagnostics=None)\n"
+ "Message(id='msg_011Cg4UECUfkHso53Kieoabs', container=None, content=[ToolUseBlock(id='toolu_01WJoB9kA8sjR17wJ8vK4VCq', caller=DirectCaller(type='direct'), input={'positive_score': 0.95, 'negative_score': 0.02, 'neutral_score': 0.03}, name='print_sentiment_scores', type='tool_use')], model='claude-haiku-5-5', role='assistant', stop_details=None, stop_reason='tool_use', stop_sequence=None, type='message', usage=Usage(cache_creation=CacheCreation(ephemeral_1h_input_tokens=0, ephemeral_5m_input_tokens=0), cache_creation_input_tokens=0, cache_read_input_tokens=0, inference_geo='global', input_tokens=772, output_tokens=90, output_tokens_details=OutputTokensDetails(thinking_tokens=0), server_tool_use=None, service_tier='standard', iterations=[{'input_tokens': 772, 'output_tokens': 90, 'cache_read_input_tokens': 0, 'cache_creation_input_tokens': 0, 'cache_creation': {'ephemeral_5m_input_tokens': 0, 'ephemeral_1h_input_tokens': 0}, 'type': 'message'}]), diagnostics=None)\n"
]
}
],
@@ -477,7 +472,7 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "Message(id='msg_011CfdhjeY447D1Vqbe82wCT', container=None, content=[ToolUseBlock(id='toolu_013MyMGb1gPE4QYJkEi9AK4g', caller=DirectCaller(type='direct'), input={'positive_score': 0.95, 'negative_score': 0.02, 'neutral_score': 0.03}, name='print_sentiment_scores', type='tool_use'), ToolUseBlock(id='toolu_01HvoHTAEER4WHpZThzWHSuB', caller=DirectCaller(type='direct'), input={'num1': 4, 'num2': 2}, name='calculator', type='tool_use')], model='claude-haiku-4-5-20251001', role='assistant', stop_details=None, stop_reason='tool_use', stop_sequence=None, type='message', usage=Usage(cache_creation=CacheCreation(ephemeral_1h_input_tokens=0, ephemeral_5m_input_tokens=0), cache_creation_input_tokens=0, cache_read_input_tokens=0, inference_geo='not_available', input_tokens=878, output_tokens=132, output_tokens_details=None, server_tool_use=None, service_tier='standard'), diagnostics=None)\n"
+ "Message(id='msg_011Cg4UEHS5DckQXLEsK4bp5', container=None, content=[ToolUseBlock(id='toolu_01B4Pdo9ceA6PAqtGNufwPyy', caller=DirectCaller(type='direct'), input={'positive_score': 0.95, 'negative_score': 0.01, 'neutral_score': 0.04}, name='print_sentiment_scores', type='tool_use'), ToolUseBlock(id='toolu_01Rciej4xSiLg62Ff4fumQTk', caller=DirectCaller(type='direct'), input={'num1': 4, 'num2': 2}, name='calculator', type='tool_use')], model='claude-haiku-5-5', role='assistant', stop_details=None, stop_reason='tool_use', stop_sequence=None, type='message', usage=Usage(cache_creation=CacheCreation(ephemeral_1h_input_tokens=0, ephemeral_5m_input_tokens=0), cache_creation_input_tokens=0, cache_read_input_tokens=0, inference_geo='global', input_tokens=783, output_tokens=157, output_tokens_details=OutputTokensDetails(thinking_tokens=0), server_tool_use=None, service_tier='standard', iterations=[{'input_tokens': 783, 'output_tokens': 157, 'cache_read_input_tokens': 0, 'cache_creation_input_tokens': 0, 'cache_creation': {'ephemeral_5m_input_tokens': 0, 'ephemeral_1h_input_tokens': 0}, 'type': 'message'}]), diagnostics=None)\n"
]
}
],
@@ -647,7 +642,7 @@
"output_type": "stream",
"text": [
"=======Claude Wants To Call The send_text_to_user Tool=======\n",
- "TEXT MESSAGE SENT: Hey! I'm doing great, thanks for asking! 👋 How can I help you today?\n"
+ "TEXT MESSAGE SENT: Hey there! I'm doing well, thanks for asking. How can I help you today? If you need help with your account or a previous purchase, please send me your username.\n"
]
}
],
@@ -674,7 +669,7 @@
"output_type": "stream",
"text": [
"=======Claude Wants To Call The send_text_to_user Tool=======\n",
- "TEXT MESSAGE SENT: I'd be happy to help you look up an order! To get started, could you please provide me with your username?\n"
+ "TEXT MESSAGE SENT: I'd be happy to help you look up your order. Could you please provide your username?\n"
]
}
],
@@ -728,7 +723,7 @@
"output_type": "stream",
"text": [
"=======Claude Wants To Call The send_text_to_user Tool=======\n",
- "TEXT MESSAGE SENT: Hey there! I'm having trouble understanding your message. Could you let me know what you need help with? I can assist you with account information or other inquiries.\n"
+ "TEXT MESSAGE SENT: Hi! I'm not sure I understood your message. It looks like it may have been sent by mistake. Could you tell me what you need help with? If you have an account question, please share your username so I can look up your information.\n"
]
}
],
diff --git a/content/github/claude-quickstarts/README.md b/content/github/claude-quickstarts/README.md
index 9cac84096b..fe0fdd1164 100644
--- a/content/github/claude-quickstarts/README.md
+++ b/content/github/claude-quickstarts/README.md
@@ -104,6 +104,12 @@ A scheduled Sentry triage agent built on Claude Managed Agents. This project dem
[Go to Managed Agents Sentry Quickstart](./managed-agents/sentry)
+### Managed Agents: Sentry Autofix
+
+A production error fixed by pull request, with Claude Managed Agents and the Sentry MCP server. This project demonstrates a webhook-driven session per Sentry issue: the agent reads the stack trace and Seer's root cause analysis, reproduces the bug with a failing test in a mounted GitHub repository, and pushes a branch, and the host opens the pull request through a custom tool so a person reviews every fix. Setup runs in Claude Code with Sentry's Agent Plugin. Credentials stay in a vault outside the sandbox, the sandbox has no route to the open internet, and each session has a hard spend cap.
+
+[Go to Managed Agents Sentry Autofix Quickstart](./managed-agents/sentry-autofix)
+
### Managed Agents: Slack
A Slack bot backed by a Claude Managed Agent. This project demonstrates a stateless webhook bridge: an `@mention` creates a Managed Agents session with the channel and thread stored in session metadata, and the `session.status_idled` webhook reads that metadata back to post the reply in-thread. There is no database and no long-lived connection.
diff --git a/content/github/claude-quickstarts/managed-agents/README.md b/content/github/claude-quickstarts/managed-agents/README.md
index 4d007cf6ce..f0e975f2a9 100644
--- a/content/github/claude-quickstarts/managed-agents/README.md
+++ b/content/github/claude-quickstarts/managed-agents/README.md
@@ -113,6 +113,18 @@ Projects built on [Claude Managed Agents](https://platform.claude.com/docs/en/ma
`mcp_oauth` credential that Anthropic injects on the MCP connection
and refreshes; the sandbox never holds a token.
+- **[sentry-autofix/](sentry-autofix/)** turns a new Sentry issue into
+ a pull request. A signed Sentry webhook starts one session per issue.
+ The agent reads the stack trace and Seer's root cause analysis
+ through the Sentry MCP server (an `mcp_oauth` vault credential),
+ reproduces the bug with a failing test in the mounted repository,
+ and pushes a branch. The host opens the pull request through a
+ custom tool, so the repository, the base branch, and the
+ `Fixes SHOP-1A` link are never the agent's to choose, and it takes
+ away the session's push access once the pull request is open. Setup
+ runs inside Claude Code with Sentry's Agent Plugin to pick the org
+ and project.
+
- **[slack/](slack/)** answers `@mentions` in Slack with a threaded
reply, over a stateless Bun webhook bridge. The Slack event creates
a session with the channel and thread stored in session `metadata`,
diff --git a/content/github/claude-quickstarts/managed-agents/sentry-autofix/CLAUDE.md b/content/github/claude-quickstarts/managed-agents/sentry-autofix/CLAUDE.md
new file mode 100644
index 0000000000..3516a6be37
--- /dev/null
+++ b/content/github/claude-quickstarts/managed-agents/sentry-autofix/CLAUDE.md
@@ -0,0 +1,85 @@
+# Sentry autofix on Claude Managed Agents
+
+Long-running Node server (Hono). Sentry posts a signed `issue` / `created` webhook → `src/app.ts` verifies it and hands the issue to `src/fixer.ts` → one Managed Agents session per issue, with the repository mounted as a `github_repository` resource, the Sentry MCP credential attached through a vault, a dollar budget, the kickoff message in `initial_events`, and `metadata.sentry_short_id` as the dedupe key → the agent reads the issue and Seer's analysis through the Sentry MCP server, reproduces, fixes, pushes `autofix/` → it calls the `open_pull_request` custom tool, which this host answers with the GitHub API. `npm run fix -- SHOP-1A` runs the same path without a webhook.
+
+```
+Sentry ──POST /webhooks/sentry──▶ app.ts (HMAC check, issue.created only)
+ │ onIssue
+ ▼
+ fixer.ts ──sessions.create──▶ session ─────────────▶ issue fixer (opus)
+ ▲ resources: github_repository bash, read, edit, grep
+ │ vault_ids: Sentry mcp_oauth sentry MCP: get_sentry_resource,
+ │ budget, metadata search_*, analyze_issue_with_seer
+ │
+ GitHub REST ◀── open_pull_request ┘◀── agent.custom_tool_use {branch, title, body}
+ (host token, host-chosen repo/base, user.custom_tool_result {PR URL | error}
+ host-written "Fixes SHOP-1A")
+```
+
+Needs `@anthropic-ai/sdk` ≥ 0.125.0, `jq`, and `ant` ≥ 1.34 (the first release whose `ant apply` manages vaults).
+
+## When the user asks to set this up, get it working, or debug it
+
+1. **Invoke `/claude-api` first.** It loads the Managed Agents API reference (agents, sessions, environments, events, vaults, MCP, permission policies). Use it as the source of truth for any SDK call you write or edit. Don't guess field names.
+2. **Use the installed Sentry plugin** (`./start.sh` installs it) to list the organizations and projects the user can access, and ask them to pick the target. Never pick a project for them. If the plugin's `sentry` MCP server is not authenticated, ask the user to run `/mcp` and sign in.
+3. **Explain the two OAuth grants** before the second sign-in: Claude Code's plugin credential serves this conversation, and the grant `npm run sentry-login` saves to the vault serves sessions that webhooks start. Never inspect or copy Claude Code's credential storage, and never put a Sentry API token in `.env`, a shell variable, or the agent prompt.
+4. **Walk the setup in this order.** Each step depends on the one before it.
+ 1. **A repository to fix.** To use the demo: copy `demo-app/` out of this checkout, make it its own repository, and push it.
+ ```bash
+ cp -r demo-app ~/sentry-autofix-demo && cd ~/sentry-autofix-demo
+ git init -b main && git add -A && git commit -m "Checkout service"
+ gh repo create sentry-autofix-demo --private --source . --push
+ ```
+ 2. **Protect the base branch.** In the repository: Settings > Rules > Rulesets > New branch ruleset, target the default branch, enable "Require a pull request before merging" and "Block force pushes", set enforcement to Active, and leave the bypass list empty. The server refuses to start without it. A classic branch protection rule does not pass: it exempts repository admins unless "Do not allow bypassing the above settings" is ticked, and the token usually belongs to an admin. If rulesets are not offered on a private repository under the user's GitHub plan, make the demo repository public.
+ 3. **A GitHub token.** Fine-grained, that one repository only, Contents: read and write, Pull requests: read and write. Leave Workflows at no access, so GitHub itself rejects a push that adds or edits a workflow file. CI that runs on every pushed branch will run the agent's branch too, before review: keep secrets out of reach of push-triggered workflows. It goes in `.env` as `GITHUB_TOKEN`.
+ 4. **Sentry.** Have the user pick the organization through the plugin. Create a Node project in it (or pick an existing one), put its slug in `.env` as `SENTRY_PROJECT`, and put its DSN in the demo app's environment as `SENTRY_DSN`. Add the GitHub integration to the Sentry organization and add the repository to it: that is what makes `Fixes SHOP-1A` link the pull request to the issue.
+ 5. **Managed Agents resources.** `ant auth login`, `npm install`, then `./agents/setup.sh`. It runs `ant apply --yes agents/issue-fixer`, which creates or updates the agent, environment, and vault and writes their IDs to `claude-lock.json` (the app reads them from there), then runs step 6 when the vault has no credential for `https://mcp.sentry.dev/mcp`. That first run waits on the user's browser consent, so give the command a long timeout or have the user run it in their own terminal. If `ant apply` prints `refusing to apply`, show the user the reason before reaching for `--force`. The lockfile records the organization and workspace, so check `ant auth status` first: applying under a different profile is refused rather than silently creating copies.
+ 6. **Sentry credential.** `npm run sentry-login` (setup runs it the first time) prints a URL. Stop while the user opens it and approves the organization. On Sentry's screen only **Inspect Issues & Events** and **Seer** stay checked. The script stores an `mcp_oauth` credential in the vault and probes it. Read back the `credential: validation status` line: `invalid` means the SSO limitation (step 5). On a remote machine the browser's redirect to `localhost:8976` fails to load: the user pastes that final URL back into the terminal.
+ 7. **Try it.** Start the demo app with `npm start`, run `npm run break` in it, find the new issue's short ID with the plugin (or in Sentry), then `npm run fix -- ` here. A fix takes a few minutes. Seer alone can take five.
+ 8. **Webhooks.** Only after the CLI path works. Sentry: Settings > Developer Settings > New Internal Integration, webhook URL `/webhooks/sentry`, then check `issue` under Webhooks. If that checkbox is disabled, the integration lacks read permission on issues and events: grant it under Permissions first. Client Secret goes in `.env` as `SENTRY_CLIENT_SECRET`. Then `npm run dev`.
+5. **Recognize the SSO limitation.** If validation says `invalid`, or the first fix fails with `mcp_authentication_failed_error` or 403s inside tool results, the organization is rejecting the user-bound MCP OAuth token (SSO enforcement or a similar policy). The org-issued token that would work needs `Authorization: Sentry-Bearer`, and the vault can only send `Bearer`. Do not loop on `npm run sentry-login`. Show the user "Known limitations" in the README.
+6. **After the base loop works, offer extensions.** Ask which the user wants.
+ - **Outcomes**: kick off with `user.define_outcome` and a rubric (new test fails before the fix, whole suite passes after, diff touches only what the root cause needs) instead of `user.message`, so a grader sends weak fixes back for another iteration.
+ - **Seer webhooks**: subscribe the integration to the `seer` resource and start the session on `seer.root_cause_completed`, passing `data.root_cause` in the kickoff, so the agent starts from Seer's finished analysis instead of waiting on it. The delivery goes through the same signature check in `src/app.ts` before anything reads it. Seer's text is derived from error data that outsiders can write, so fence it in the kickoff as untrusted data the way `kickoff()` fences the issue title.
+ - **`SessionToolRunner`**: `client.beta.sessions.events.toolRunner(sessionId, {tools})` replaces the hand-written loop in `drive()`. It reconnects dropped streams. It does not report `budget_reached` or `retries_exhausted` stops or the agent's final message, which is why this quickstart reads the stream itself.
+ - **Hear about a lapsed grant**: register a webhook for `vault_credential.refresh_failed`, so a failed refresh reaches a person before the next issue's session fails on it.
+ - **Tell the team**: post the pull request URL to Slack from the `pr_opened` branch in `handleCustomTool`. The host posts it, with text the host writes. Don't give the session a Slack tool.
+ - **A feature flag instead of a wait**: give the agent a second custom tool that asks to turn off a LaunchDarkly flag for the broken code path while the pull request waits for review. Keep it host-side like `open_pull_request`, with the flag key fixed in config, and have the host wait for a person to approve (a Slack button, a CLI prompt) before it calls LaunchDarkly. Anyone who can trigger an error can start a session, so an unapproved flag flip would let an outsider switch off a feature by sending bad requests. A pull request has a reviewer in front of it. A flag change does not unless you put one there.
+ - **Schedule instead of webhooks**: a scheduled deployment that runs `search_issues` for new unresolved issues each hour. See `/claude-api`, scheduled deployments.
+
+## Design rules to keep when editing
+
+- The agent's shell is `always_allow` and reads attacker-writable text. Anything that could widen what it reaches (a new `allowed_hosts` entry, an enabled web tool, `update_issue`, `execute_sentry_tool`) needs the same scrutiny as handing a stranger that capability.
+- Host-side tools decide the repository, the base branch, and the issue link. Never take those from tool input.
+- `drive()` is one code path for a first connect, a reconnect, and a restarted host: open the stream, replay `events.list`, tail. Keep new event handling idempotent against replay, the way the `answered` set keeps a tool call from being answered twice.
+- Log tool names, never tool inputs. Inputs are derived from production error data.
+- `hasClosingReference` in `src/github.ts` mirrors Sentry's parser (`src/sentry/utils/groupreference.py` in getsentry/sentry) and GitHub's keyword rule. Sentry's reference span runs through plain words and newlines until punctuation, so text the host writes into a pull request uses the verbs fix, close, and resolve exactly once, in `Fixes .`, and that line ends with a period.
+- `mcp_servers[].url` in `agent.yaml`, `SENTRY_MCP_URL` in `src/fixer.ts` (which `src/sentry-login.ts` imports), and the URL `agents/setup.sh` greps for must be the same string. The platform matches credentials to servers by URL.
+- `SCOPES` in `src/sentry-login.ts` is narrower than what the server advertises, and the script refuses a token that reports more. The tool allow-list in `agent.yaml` can drift in the Console, so it is not the only bound on what the credential can do.
+
+## Debugging
+
+| Symptom | Cause | Fix |
+|---|---|---|
+| Server exits: "is not protected" or "classic branch protection rule but no ruleset" | No active ruleset requires a pull request for `GITHUB_BASE_BRANCH`. A ruleset in Evaluate mode does not count, and neither does a classic rule | Step 4.2, with enforcement set to Active |
+| `ant apply` cannot tell what kind of resource `vault.yaml` is | The file lost its `type: vault` line, or `ant` is older than 1.34 | Restore the line, or upgrade `ant` |
+| Startup says `claude-lock.json` is missing or has no agent | `./agents/setup.sh` has not run in this directory, or the lockfile was deleted | Run it. If the resources still exist, `ant apply` would create new ones: archive the old ones in the Console |
+| Server exits: "no Sentry credential" | `npm run sentry-login` never ran, or ran against a different vault | Run it again. It replaces the old credential |
+| `mcp_authentication_failed_error` on the first fix, or `sentry-login` prints `validation status invalid` | The organization rejects the user-bound MCP OAuth token (SSO enforcement or a similar policy), or the credential URL does not match `agent.yaml` | Check the URLs match. If they do, signing in again will not help: see "Known limitations" in the README |
+| `mcp_authentication_failed_error` after fixes that used to work | Refresh failed: the grant was revoked or the Sentry session behind it lapsed. `ant beta:vaults:credentials mcp-oauth-validate` shows the failing step | `npm run sentry-login` |
+| 403 from Sentry inside a tool result | The grant lacks the skill, or the organization rejects user-bound OAuth tokens | `npm run sentry-login` and approve **Inspect Issues & Events** and **Seer**. If it persists, see "Known limitations" in the README |
+| `sentry-login` says Sentry "granted more than this quickstart asked for" | The token reports a scope outside `SCOPES` in `src/sentry-login.ts` | Nothing was stored, and the old credential is untouched. Read which scope the message names before widening `SCOPES` |
+| `mcp_egress_blocked_error` | `allow_mcp_servers: true` is missing from `environment.yaml` | Restore it and re-run `./agents/setup.sh` |
+| Session never calls a Sentry tool, or parks waiting for a confirmation | The tools were disabled or set to `always_ask` in the Console after an agent update | Set the five tools back to enabled and always allow in the Console |
+| Hosted Sentry MCP rejects a pasted API token | It accepts user tokens only as `Authorization: Sentry-Bearer`, and a `static_bearer` vault credential sends `Bearer` | Use `npm run sentry-login` (OAuth). Don't switch the credential type |
+| Webhook returns 401 | `SENTRY_CLIENT_SECRET` is from a different integration, or a proxy re-serialized the body | Copy the Client Secret again. The signature covers the exact bytes Sentry sent |
+| Webhook returns `{"ignored": true}` | Not `issue` / `created`, or `SENTRY_PROJECT` does not match the issue's project slug | Expected for other events. Check the slug |
+| "already has a session" or "has ended" | This process is already driving a session with this `sentry_short_id`, or that session is terminated | Wait for it, or archive it (Console, or `ant beta:sessions archive --session-id ... < /dev/null`) to run the issue again |
+| Log says "(picked back up)" | A session for the issue existed with no driver, because the host restarted or lost its stream. `drive()` replayed the event log and carried on | Nothing. This is the recovery path |
+| Log says "fixes are already running" | `AUTOFIX_MAX_ACTIVE` sessions are in flight, and the new issue was skipped. Sentry does not redeliver | `npm run fix -- ` once there is room, or raise the limit |
+| `open_pull_request` error names a commit that "would close or resolve an issue" | A commit message has fix, close, or resolve followed by an issue reference, or by a hyphenated word Sentry would read as a short ID (`Fix off-by-one`). The agent prompt asks for other verbs, so this is a slip or an injection | The agent recreates the commits on a new branch. If it keeps happening, read the Sentry event for injected text |
+| Pull request closed with a comment from the autofix host | The end-of-session recheck failed closed. Either commits landed after the pull request opened and no longer pass inspection (only possible if revoking push access failed: look for "could not revoke push access" in the log), or GitHub could not be read three times in a row | The comment says which. For the first, read those commits and the Sentry event. For the second, check the commits and reopen the pull request |
+| Run ends `failed`, note `stopped: budget_reached` | The session hit `AUTOFIX_MAX_USD` | Raise it for new sessions, or raise the paused session's budget in the Console to resume it |
+| `open_pull_request` error "No commits between" | The push failed or went to another branch | Read the session in the Console. A rejected push to the base branch is the protection working |
+| Pull request merged, issue still open in Sentry | Sentry resolves on the next release that contains the commit, not on merge | Create a release with commits associated, or resolve it by hand |
+| `npm install` 404s in `demo-app/` behind a corporate mirror | The mirror lacks `@sentry/node` 10's newer dependencies | `npm install @sentry/node@9`. The two calls the demo uses are the same in 9 and 10 |
diff --git a/content/github/claude-quickstarts/managed-agents/sentry-autofix/README.md b/content/github/claude-quickstarts/managed-agents/sentry-autofix/README.md
new file mode 100644
index 0000000000..97d98142ed
--- /dev/null
+++ b/content/github/claude-quickstarts/managed-agents/sentry-autofix/README.md
@@ -0,0 +1,122 @@
+# Sentry × Claude Managed Agents: fix production errors with a pull request
+
+A new error lands in [Sentry](https://sentry.io/). A [Managed Agents](https://platform.claude.com/docs/en/managed-agents/overview) session reads the stack trace and [Seer](https://docs.sentry.io/product/ai-in-sentry/seer/)'s root cause analysis through the [Sentry MCP server](https://mcp.sentry.dev/), reproduces the bug with a failing test in a clone of your repository, fixes it, and opens a pull request that says `Fixes SHOP-1A`. You review and merge. Sentry resolves the issue when a release contains the merge commit.
+
+The host is about 600 lines of TypeScript: a webhook route, one `sessions.create` per issue, a loop that answers the agent's one custom tool, and a Sentry OAuth login helper. It stores nothing. A session's metadata says which issue it is for and its event log says how far the fix got. Webhook retries don't start a second fix, and a host that restarted mid-fix picks the session back up the next time the issue is delivered or you run `npm run fix` for it.
+
+`demo-app/` is a small Express checkout service with a real bug to try it on: any cart without a coupon code returns a 500.
+
+## Quickstart
+
+Needs:
+
+- [Claude Code](https://docs.claude.com/en/docs/claude-code), for the guided setup
+- Node 22.9 or later
+- The [`ant` CLI](https://platform.claude.com/docs/en/cli-sdks-libraries/cli/quickstart) 1.34 or later (`brew install anthropics/tap/ant`), `jq`, and Anthropic auth: `ant auth login` once, or an API key from [platform.claude.com](https://platform.claude.com/)
+- A Sentry organization. Seer is a paid add-on. Without it the agent works from the stack trace alone and says so in the pull request.
+- A GitHub repository whose default branch has a [ruleset](https://docs.github.com/en/repositories/configuring-branches-and-merges-in-your-repository/managing-rulesets/about-rulesets) that requires a pull request, and a [fine-grained token](https://github.com/settings/personal-access-tokens) for that one repository with Contents and Pull requests set to read and write. Leave its Workflows permission off
+
+```bash
+cd managed-agents/sentry-autofix
+./start.sh
+```
+
+`start.sh` installs or updates [Sentry's Agent Plugin for Claude Code](https://docs.sentry.io/ai/agent-plugin/) at project scope (`.claude/settings.json` records it), then starts Claude with the walkthrough in [`CLAUDE.md`](CLAUDE.md). The plugin gives the setup conversation an authenticated Sentry MCP connection. Claude lists your organizations and projects for you to choose from, and later finds the demo issue's short ID.
+
+You authorize Sentry twice, because two clients hold separate credentials:
+
+1. **The plugin.** If Claude reports the plugin's `sentry` server as unauthenticated, run `/mcp` inside Claude Code and sign in. Claude Code owns that OAuth session and doesn't share it.
+2. **The vault.** Sessions that a webhook starts need their own credential. `./agents/setup.sh` runs `npm run sentry-login`, which prints a URL, obtains a grant with PKCE, and writes the access and refresh tokens to an Anthropic vault. No Sentry token goes into `.env`, a command-line argument, or the agent prompt.
+
+On Sentry's approval screen for the second one, leave only **Inspect Issues & Events** and **Seer** checked. `sentry-login` requests three of the five scopes the server offers (`org:read`, `project:write`, `event:write`) and refuses to store a token that reports a scope outside them. The agent separately allowlists five MCP tools: `get_sentry_resource`, `find_organizations`, `search_issues`, `search_events`, and `analyze_issue_with_seer`.
+
+### By hand
+
+```bash
+ant auth login # or put ANTHROPIC_API_KEY in .env (cp .env.example .env)
+npm install
+./agents/setup.sh # `ant apply` creates the agent, environment, and vault, then `npm run sentry-login` stores the OAuth credential
+$EDITOR .env # GITHUB_REPO_URL, GITHUB_TOKEN, SENTRY_CLIENT_SECRET
+npm run fix -- SHOP-1A # fix one issue by its Sentry short ID, no webhook needed
+npm run dev # or listen on http://localhost:3000/webhooks/sentry for new issues
+```
+
+For webhooks, [create an internal integration](https://docs.sentry.io/integrations/integration-platform/) in Sentry (Settings > Developer Settings), subscribe it to the `issue` resource, and set its webhook URL to a tunnel that points at port 3000. Sentry [signs each delivery](https://docs.sentry.io/integrations/integration-platform/webhooks/) with the integration's Client Secret, so copy that to `SENTRY_CLIENT_SECRET`. [`CLAUDE.md`](CLAUDE.md) has the full walkthrough, including publishing `demo-app/` to a repository of your own and connecting it to Sentry.
+
+To change the agent (model, prompt, tools), edit [`agents/issue-fixer/agent.yaml`](agents/issue-fixer/agent.yaml) and re-run `./agents/setup.sh`. [`ant apply`](https://platform.claude.com/docs/en/cli-sdks-libraries/cli/apply) updates what changed and records the IDs in `claude-lock.json`, which the app reads. A re-run keeps the Sentry credential the vault already has. The lockfile is ignored here because its IDs belong to your organization. In your own project, commit it so teammates and CI update the same resources.
+
+## The pull request is the checkpoint
+
+Nobody watches a session that a webhook started at 3am, so the agent's shell runs without per-command approval. The sandbox also reads error text that anyone who can send your service a request can write. Four things bound what an injected instruction could do:
+
+- **A ruleset on the base branch.** The sandbox can push, so the server checks at startup that an active ruleset requires a pull request for `GITHUB_BASE_BRANCH`, and exits if none does. Without it, `git push origin HEAD:main` would skip your review, and Sentry would resolve the issue on the next release. A classic branch protection rule is not accepted: it exempts repository admins by default, and your token is usually an admin's.
+- **The host opens the pull request.** `open_pull_request` is a custom tool that this server answers with its own GitHub token. The repository, the base branch, and the `Fixes` line come from the server's config and the webhook. The host checks the agent's text the way Sentry's and GitHub's own parsers read it. A title or body that would close another issue (`Closes #12`, or `Fix the crash` with `BILLING-7` a few words later) is defused, and a branch whose commit messages would do it is refused. So is a branch that changes anything under `.github/`: a workflow file added on a pushed branch can run in GitHub Actions before anyone reviews it. Once the pull request is open the host replaces the session's repository token, so the session can't push again. As a backstop it inspects the branch once more when the session ends and closes the pull request if later commits would not pass or the branch can't be read.
+- **Credentials stay outside the sandbox.** The GitHub token is injected by a git proxy and the Sentry tokens by the MCP proxy. Code in the session can use both and read neither.
+- **No route out.** The environment denies egress except GitHub, package registries, and the Sentry MCP server. The web tools are off. Of Sentry's tools, only the ones that read (plus Seer) are enabled, so the agent can't resolve or reassign issues itself.
+
+Each session also has a hard spend cap (`AUTOFIX_MAX_USD`, default $10 at list prices). A session that reaches it pauses. `AUTOFIX_MAX_ACTIVE` (default 3) limits how many fixes run at once, so a burst of new issues is logged and skipped instead of multiplying that cap.
+
+## Credential lifecycle and re-authentication
+
+Anthropic refreshes the Sentry token for you. You sign in again only when the refresh fails.
+
+The vault credential holds the Sentry MCP server's access token and refresh token. Before a session connects, Anthropic checks the access token. If it has expired, Anthropic exchanges the refresh token at the token endpoint recorded in the credential.
+
+That exchange stops working when someone revokes the grant in Sentry, the Sentry session behind it lapses, or Sentry rejects the refresh token. The next session then fails with `mcp_authentication_failed_error`, and any webhook you have registered receives `vault_credential.refresh_failed`. `npm run sentry-login` archives the old credential and stores a new one:
+
+```bash
+npm run sentry-login
+```
+
+To check the credential at any time (the vault ID is in `claude-lock.json` under `./agents/issue-fixer/vault.yaml`):
+
+```bash
+ant beta:vaults:credentials list --vault-id # find the credential ID
+ant beta:vaults:credentials mcp-oauth-validate \
+ --vault-id --credential-id
+# status: valid | invalid | unknown, with the failing refresh or MCP step
+```
+
+`sentry-login` runs the same probe right after it stores the credential and prints `credential: validation status `.
+
+## Known limitations
+
+### Organizations that enforce SSO or reject user-bound OAuth tokens
+
+This quickstart can't read issues from an organization that rejects user-bound OAuth tokens, and signing in again doesn't help.
+
+The vault presents every MCP credential, `mcp_oauth` and `static_bearer` alike, as `Authorization: Bearer `. Neither type has a field for a different scheme. On Sentry's hosted MCP server, `Bearer` means a token minted by the server's own OAuth flow. That token is bound to the user who approved it and inherits that user's standing in the organization: SSO link, 2FA, membership. Organizations with enforced SSO or similar identity policies can reject such tokens on every API call.
+
+Consent completes and the credential saves. The failure shows up later as one of:
+
+- an `invalid` status from the probe `sentry-login` runs
+- `mcp_authentication_failed_error` on the session
+- 403 from Sentry inside the MCP tool results
+
+Those organizations expect unattended automation to use an organization-issued token (an org auth token or an internal integration token), which isn't tied to a user's session. The hosted MCP server accepts those only as `Authorization: Sentry-Bearer `. That scheme is a fixed property of `mcp.sentry.dev`, not something an organization configures, and the vault can't send it. The [Sentry triage quickstart](../sentry#known-limitations) has the same limitation and records the test that showed it.
+
+The plugin in Claude Code is unaffected, because Claude Code holds that OAuth session itself. Sentry's REST API does accept `Bearer` for org auth tokens, so an agent can reach it from the sandbox with an `environment_variable` vault credential instead of MCP, once `sentry.io` is in the environment's `allowed_hosts`. That agent has no MCP tools, so no Seer. An earlier revision of the triage quickstart shows that pattern: `git show 97c825e:managed-agents/sentry/README.md`.
+
+### MCP tool permissions after agent updates
+
+A tool permission that drifts to `always_ask` parks the session, because nobody is there to answer, and no pull request opens. After `ant apply` publishes a new agent version, check in the Managed Agents Console that the five Sentry MCP tools are still enabled with **always allow** and that the rest remain disabled.
+
+## Before you deploy
+
+`GET /` lists the fixes this process has started, including the agent's summary of each, and has no auth. The server binds loopback by default for that reason. Expose only `/webhooks/sentry` through your tunnel or proxy, and keep `HOST` on `127.0.0.1` unless you put auth in front of the rest.
+
+## Files
+
+| | |
+|---|---|
+| `start.sh` | Installs or updates the Claude Code Sentry plugin, then launches the guided setup |
+| `.claude/settings.json` | Enables the plugin at project scope |
+| `agents/issue-fixer/` | The agent, environment, and vault definitions `ant apply` keeps in sync |
+| `agents/setup.sh` | `ant apply`, then `npm run sentry-login` if the vault has no Sentry credential |
+| `src/app.ts` | The webhook route: signature check, filtering, 202 |
+| `src/fixer.ts` | One session per issue, the event loop, the `open_pull_request` handler, startup checks |
+| `src/github.ts` | Branch protection check, pull request creation |
+| `src/sentry.ts` | Webhook signature and payload parsing |
+| `src/sentry-login.ts` | MCP OAuth (discovery, dynamic registration, PKCE) into an `mcp_oauth` vault credential, then a validation probe |
+| `demo-app/` | The buggy checkout service, instrumented with `@sentry/node` |
+| `CLAUDE.md` | Full setup walkthrough, debugging table, extensions |
diff --git a/content/mcp/community/sep-guidelines.md b/content/mcp/community/sep-guidelines.md
index fd74f4b34e..9c6c5eb5a2 100644
--- a/content/mcp/community/sep-guidelines.md
+++ b/content/mcp/community/sep-guidelines.md
@@ -43,7 +43,7 @@ There are four kinds of SEP:
1. **Standards Track** - Describes a new feature or implementation for the Model Context Protocol, or an interoperability standard supported outside the core specification.
2. **Informational** - Describes a design issue or provides guidelines/information to the community without proposing a new feature.
3. **Process** - Describes a process surrounding MCP or proposes a change to a process (like this document).
-4. **Extensions Track** - Describes a protocol extension. Follows the same review and acceptance process as Standards Track SEPs, but indicates that the proposal is for an extension rather than a protocol addition. See [Creating Extensions](https://modelcontextprotocol.io/extensions/overview.md#creating-extensions) for the extension lifecycle.
+4. **Extensions Track** - Describes a protocol extension. Follows the same review and acceptance process as Standards Track SEPs, but indicates that the proposal is for an extension rather than a protocol addition. An accepted Extensions Track SEP moves an extension to Beta, and a second one moves it to Stable. See [Extension Lifecycle](https://modelcontextprotocol.io/extensions/overview.md#extension-lifecycle) for the stages.
## SEP Workflow
diff --git a/content/mcp/extensions/overview.md b/content/mcp/extensions/overview.md
index 3ffc6cc363..40c53bf76c 100644
--- a/content/mcp/extensions/overview.md
+++ b/content/mcp/extensions/overview.md
@@ -16,9 +16,23 @@ Extensions are identified using a unique *extension identifier* with the format:
>
> If you're building a third-party extension, use a reversed domain name you own as the vendor prefix to avoid collisions (similar to Java package naming). For example, a company owning `example.com` would use `com.example/` as their prefix (e.g., `com.example/my-extension`).
+## Extension Lifecycle
+
+Every extension is at one of three stages, and may later be promoted into the core specification. The stage decides which changes are allowed, who approves them, and what implementers can expect. For full details, see [SEP-3392: Extension Lifecycle](https://modelcontextprotocol.io/seps/3392-extension-lifecycle.md).
+
+| Stage | Protocol changes | Changes approved by | Entry | What implementers can expect |
+| - | - | - | - | - |
+| **Experimental** | Any change, at any time, without notice | Extension Maintainer | Added by an Extension Maintainer | Nothing. The design may change or disappear. |
+| **Beta** | Any change, with breaking changes expected to be rare | Extension Maintainer | Extensions Track SEP | Real usage is welcome. Breaking changes are documented. |
+| **Stable** | Only with a new core protocol revision | Extension Maintainer | Second Extensions Track SEP | Behavior is fixed within a protocol revision. |
+
+An extension starts as Experimental and must pass through Beta. From Beta it either becomes Stable, or a Standards Track SEP promotes it into the core specification. A Stable extension can also be promoted later. Each Beta extension states its intended destination, Stable or Core, which may change while it is in Beta.
+
+An extension's identifier does not change when its stage changes.
+
## Official Extension Repositories
-Official extensions live inside the [Model Context Protocol GitHub organization](https://github.com/modelcontextprotocol/) in repositories with the `ext-` prefix.
+Official extensions live inside the [Model Context Protocol GitHub organization](https://github.com/modelcontextprotocol/) in repositories with the `ext-` prefix. One repository can hold several related extensions at different stages. Inside the repository, the directory that holds an extension's specification shows its stage: `specification/experimental/`, `specification/beta/` or `specification/stable/`. Extensions that were promoted to the core specification or have ended move to `specification/archived/`.
### MCP Authorization Extensions
@@ -27,10 +41,10 @@ Official extensions live inside the [Model Context Protocol GitHub organization]
> Extensions for supplementary authorization mechanisms beyond the core
> specification.
-| Extension | Description |
-| - | - |
-| [OAuth Client Credentials](https://modelcontextprotocol.io/extensions/auth/oauth-client-credentials.md) | OAuth 2.0 client credentials flow for machine-to-machine authentication. |
-| [Enterprise-Managed Authorization](https://modelcontextprotocol.io/extensions/auth/enterprise-managed-authorization.md) | Framework for enterprise environments requiring centralized access control. |
+| Extension | Stage | Description |
+| - | - | - |
+| [OAuth Client Credentials](https://modelcontextprotocol.io/extensions/auth/oauth-client-credentials.md) | Stable | OAuth 2.0 client credentials flow for machine-to-machine authentication. |
+| [Enterprise-Managed Authorization](https://modelcontextprotocol.io/extensions/auth/enterprise-managed-authorization.md) | Stable | Framework for enterprise environments requiring centralized access control. |
### MCP Apps
@@ -38,17 +52,21 @@ Official extensions live inside the [Model Context Protocol GitHub organization]
>
> Extensions for interactive UI elements in conversational MCP clients.
-| Extension | Description |
-| - | - |
-| [MCP Apps](https://modelcontextprotocol.io/extensions/apps/overview.md) | Allows MCP Servers to display interactive UI elements (charts, forms, video players) inline within conversations |
+| Extension | Stage | Description |
+| - | - | - |
+| [MCP Apps](https://modelcontextprotocol.io/extensions/apps/overview.md) | Stable | Allows MCP Servers to display interactive UI elements (charts, forms, video players) inline within conversations |
To get started building MCP Apps, see the [quickstart guide](https://modelcontextprotocol.io/extensions/apps/build.md#getting-started) or read the full [MCP Apps documentation](https://apps.extensions.modelcontextprotocol.io/api/documents/Quickstart.html).
### MCP Tasks
-| Extension | Description |
-| - | - |
-| [MCP Tasks](https://modelcontextprotocol.io/extensions/tasks/overview.md) | Asynchronous task execution for long-running operations, with polling, mid-flight input, and durable handles. |
+> **[modelcontextprotocol/ext-tasks](https://github.com/modelcontextprotocol/ext-tasks)**
+>
+> Extensions for long-running operations.
+
+| Extension | Stage | Description |
+| - | - | - |
+| [MCP Tasks](https://modelcontextprotocol.io/extensions/tasks/overview.md) | Beta, to Core | Asynchronous task execution for long-running operations, with polling, mid-flight input, and durable handles. |
### Skills over MCP
@@ -56,43 +74,50 @@ To get started building MCP Apps, see the [quickstart guide](https://modelcontex
>
> Discover and read Agent Skills from MCP servers.
-| Extension | Description |
-| - | - |
-| [Skills over MCP](https://modelcontextprotocol.io/extensions/skills/overview.md) | Discover workflow instructions and read supporting files through MCP resources. |
+| Extension | Stage | Description |
+| - | - | - |
+| [Skills over MCP](https://modelcontextprotocol.io/extensions/skills/overview.md) | Beta, destination not yet stated | Discover workflow instructions and read supporting files through MCP resources. |
See the [Skills overview](https://modelcontextprotocol.io/extensions/skills/overview.md) to get started and the
[client matrix](https://modelcontextprotocol.io/extensions/client-matrix.md) for implementation support.
+### MCP Server Cards
+
+> **[modelcontextprotocol/ext-server-card](https://github.com/modelcontextprotocol/ext-server-card)**
+>
+> HTTP discovery of MCP server metadata.
+
+| Extension | Stage | Description |
+| - | - | - |
+| [Server Cards](https://modelcontextprotocol.io/seps/2127-mcp-server-cards.md) | Beta, destination not yet stated | Lets clients discover a server's metadata before connecting to it. |
+
## Experimental Extensions
-Experimental extensions provide an incubation pathway for [Working Groups and Interest Groups](https://modelcontextprotocol.io/community/working-interest-groups.md) to prototype ideas and collaborate on extension concepts before formal SEP submission.
+Experimental extensions provide an incubation pathway for [Working Groups and Interest Groups](https://modelcontextprotocol.io/community/working-interest-groups.md) to prototype ideas and collaborate on extension concepts before or alongside a SEP.
-Experimental extension repositories live within the MCP GitHub organization with the `experimental-ext-` prefix (e.g., `experimental-ext-interceptors`).
+An Experimental extension lives either under `specification/experimental/` in an existing `ext-` repository, or in its own repository with the `experimental-ext-` prefix (e.g., `experimental-ext-interceptors`). Everything in an `experimental-ext-` repository is Experimental.
### Ground Rules
* Every experimental extension needs to be associated with a Working Group or Interest Group
-* Repositories and published packages need to clearly indicate their experimental status (e.g., in the README and package name)
-* [Core Maintainers](https://modelcontextprotocol.io/community/contributor-ladder.md#core-maintainer) retain oversight of experimental extension repositories, including the ability to archive or remove them
-
-### Graduation to Official Status
-
-To promote an experimental extension to official status, it goes through the standard SEP process (Extensions Track). Feel free to reference the experimental repository and any reference implementations you built during incubation to demonstrate the extension's practicality.
+* Published packages need to clearly indicate their experimental status (e.g., in the README and package name)
+* Implementers should pin to a tag or commit, because two revisions of an Experimental extension need not be compatible
+* [Core Maintainers](https://modelcontextprotocol.io/community/contributor-ladder.md#core-maintainer) retain oversight of experimental extensions, including the ability to archive or remove them
## Creating Extensions
-The lifecycle for official extensions follows a SEP-based process. For full details, see [SEP-2133: Extensions](https://modelcontextprotocol.io/seps/2133-extensions.md).
-
-1. **Propose**: Create a SEP in the main MCP repository using the [standard SEP guidelines](https://modelcontextprotocol.io/community/sep-guidelines.md) with type **Extensions Track**.
-2. **Implement**: Build at least one reference implementation in an official SDK — this is required before the SEP can be reviewed.
-3. **Review**: [Core Maintainers](https://modelcontextprotocol.io/community/contributor-ladder.md#core-maintainer) review the SEP and have final authority over inclusion.
-4. **Publish**: Once approved, open a PR to add the extension to the extension repository.
-5. **Adopt**: After that, other clients, servers, and SDKs can implement the extension too.
+1. **Prototype**: Add the extension under `specification/experimental/` in an `ext-` repository, or create an `experimental-ext-` repository.
+2. **Propose Beta**: Create a SEP in the main MCP repository using the [standard SEP guidelines](https://modelcontextprotocol.io/community/sep-guidelines.md) with type **Extensions Track**. State whether the extension is intended to become Stable or to be promoted to Core.
+3. **Implement**: Build at least one reference implementation in an official SDK. This is required before the SEP can be reviewed.
+4. **Review**: [Core Maintainers](https://modelcontextprotocol.io/community/contributor-ladder.md#core-maintainer) review the SEP and have final authority over inclusion.
+5. **Publish**: Once the SEP is accepted, open a PR that moves the extension to `specification/beta/` in an `ext-` repository. A Core Maintainer approves the move.
+6. **Gather evidence**: During Beta, keep a public list of known implementations and the feedback received from them.
+7. **Stabilize or promote**: A second Extensions Track SEP moves the extension to Stable. It needs two independent, interoperating implementations (one client-side, one server-side) and a [conformance scenario](https://modelcontextprotocol.io/community/sep-guidelines.md#conformance-test-requirement). Alternatively, a Standards Track SEP promotes the extension into the core specification.
### Requirements
* Extension specifications need to use RFC 2119 language (MUST, SHOULD, MAY)
-* Extensions must have an associated working group or interest group
+* Extensions must have an associated working group or interest group, and at least one Extension Maintainer listed in the repository's `MAINTAINERS.md`
### SDK Implementation
@@ -100,13 +125,17 @@ SDKs can choose to implement extensions, but it's not required for protocol conf
> [!NOTE]
>
-> Extensions are always disabled by default and require explicit opt-in from the developer.
+> Extensions are always disabled by default and require explicit opt-in from the developer, at every stage.
### Evolution
-Extensions evolve independently of the core protocol. Updates are managed by the extension repository maintainers and don't require core maintainer review.
+Changes to an extension are approved by its Extension Maintainers and don't require Core Maintainer review. What may change depends on the stage:
+
+* **Experimental**: anything, at any time.
+* **Beta**: prefer additive changes, such as new optional fields or capability flags in the settings object. Breaking changes are allowed but should be rare and batched, announced in the Working Group or Interest Group first, and recorded in a changelog. An extension that makes a breaking change should add or increment a `revision` string in its settings object, so that peers can detect a mismatch.
+* **Stable**: published as revisions keyed to core protocol revisions, such as `specification/stable//2026-07-28/`. A published revision is immutable. Changes accumulate in a `draft/` directory and take effect only with a new core protocol revision. The behavior of the extension for a pair of peers is the behavior defined for the protocol revision they negotiate.
-That said, backwards compatibility matters. When you need to change an extension, prefer using capability flags or versioning within the extension settings object rather than creating a new extension identifier. If a breaking change is unavoidable, use a new identifier (e.g., `io.modelcontextprotocol/my-extension-v2`).
+Breaking changes keep the extension's identifier. A new identifier (e.g., `io.modelcontextprotocol/my-extension-v2`) is used only when old and new behavior must coexist under one protocol revision.
A **breaking change** is any modification that would cause existing implementations to fail or behave incorrectly, including:
@@ -115,6 +144,10 @@ A **breaking change** is any modification that would cause existing implementati
* Altering the semantics of existing behavior
* Adding new required fields
+### Promotion to Core
+
+When a Standards Track SEP promotes an extension into the core specification in protocol revision R, the feature is core behavior for requests that declare R or later, whether or not the extension is advertised. For earlier revisions, the extension's final revision still applies, so a client that supports earlier revisions should keep advertising the extension. The extension's specification moves to `specification/archived/` once R is released.
+
## Negotiation
Clients and servers advertise their support for extensions in the `extensions` field within their respective capability declarations.
diff --git a/content/mcp/seps.md b/content/mcp/seps.md
index c34d41e970..a1bae842e1 100644
--- a/content/mcp/seps.md
+++ b/content/mcp/seps.md
@@ -17,13 +17,14 @@ Each SEP is reachable by number at `/seps/` (for example, [/seps/1850](h
## Summary
* **Accepted**: 1
-* **Final**: 43
+* **Final**: 44
## All SEPs
| SEP | Title | Status | Type | Created |
| - | - | - | - | - |
| [SEP-3398](https://modelcontextprotocol.io/seps/3398-release-cycle-updates.md) | Release Cycle Updates | Accepted | Process | 2026-09-17 |
+| [SEP-3392](https://modelcontextprotocol.io/seps/3392-extension-lifecycle.md) | Extension Lifecycle | Final | Process | 2026-09-25 |
| [SEP-2663](https://modelcontextprotocol.io/seps/2663-tasks-extension.md) | Tasks Extension | Final | Extensions Track | 2026-04-27 |
| [SEP-2640](https://modelcontextprotocol.io/seps/2640-skills-extension.md) | Skills Extension | Final | Extensions Track | 2026-04-23 |
| [SEP-2596](https://modelcontextprotocol.io/seps/2596-spec-feature-lifecycle-and-deprecation.md) | Specification Feature Lifecycle and Deprecation Policy | Final | Process | 2026-04-17 |
diff --git a/content/mcp/seps/3392-extension-lifecycle.md b/content/mcp/seps/3392-extension-lifecycle.md
new file mode 100644
index 0000000000..6ead723ffa
--- /dev/null
+++ b/content/mcp/seps/3392-extension-lifecycle.md
@@ -0,0 +1,300 @@
+> ## Documentation Index
+> Fetch the complete documentation index at: https://modelcontextprotocol.io/llms.txt
+> Use this file to discover all available pages before exploring further.
+
+# SEP-3392: Extension Lifecycle
+
+> Extension Lifecycle
+
+Final
+
+Process
+
+> [!NOTE]
+>
+> This SEP has reached Final status and is preserved as a historical record of
+> the design as accepted. Changes made to the protocol after finalization are
+> not reflected here. Refer to the [current
+> specification](https://modelcontextprotocol.io/specification/latest.md) and its changelog for authoritative
+> requirements.
+
+| Field | Value |
+| - | - |
+| **SEP** | 3392 |
+| **Title** | Extension Lifecycle |
+| **Status** | Final |
+| **Type** | Process |
+| **Created** | 2026-09-25 |
+| **Author(s)** | Peter Alexander ([@pja-ant](https://github.com/pja-ant)) |
+| **Sponsor** | [@pja-ant](https://github.com/pja-ant) |
+| **PR** | [#3392](https://github.com/modelcontextprotocol/modelcontextprotocol/pull/3392) |
+
+***
+
+## Abstract
+
+This SEP gives MCP extensions a maturity lifecycle. An extension starts as Experimental, may advance to Beta, and then either becomes Stable as an extension or is promoted into the core specification. The directory that holds the extension's specification shows the stage (`specification/experimental/`, `specification/beta/`, `specification/stable/`). One `ext-` repository can therefore hold extensions at different stages, and no repository is renamed when a stage changes. The stage decides which protocol changes are allowed, who approves them, and what stability implementers can expect.
+
+Experimental and Beta extensions iterate with Extension Maintainer approval only, and may make breaking changes. Entering Beta and entering Stable each require an Extensions Track SEP. A Stable extension changes only when a new core protocol revision is released. Promotion to the
+core specification requires a Standards Track SEP.
+
+This SEP updates the extension lifecycle defined in [SEP-2133](https://modelcontextprotocol.io/seps/2133-extensions.md). It does not change how extensions are negotiated.
+
+## Motivation
+
+SEP-2133 defines two kinds of extension: an experimental extension in an `experimental-ext-` repository with no stability promise, and an official extension in an `ext-` repository that graduated through an Extensions Track SEP. It has no notion of maturity, and two problems
+follow.
+
+**Official extensions carry no stability signal.** An Extensions Track SEP is the only gate, and once an extension is official, SEP-2133 lets its maintainers change it at any time without Core Maintainer review. An implementer cannot tell whether an official extension is settled
+or still being reworked. Extensions signal maturity in different, undefined words: `ext-auth` uses `specification/stable/` and `specification/draft/`, `ext-tasks` labels its schema snapshots "Stable" and "Development", and `ext-skills` publishes `specification/stable/`.
+
+**Change points for official extensions are undefined.** SEP-2133 lets extension maintainers change an official extension whenever they choose, and requires a new identifier for every breaking change. Implementers need predictable moments when behavior may change. The protocol
+already provides one, because every request declares a protocol revision, and [SEP-2663](https://modelcontextprotocol.io/seps/2663-tasks-extension.md) already defines extension behavior per protocol revision.
+
+[SEP-2596](https://modelcontextprotocol.io/seps/2596-spec-feature-lifecycle-and-deprecation.md) left "feature maturity tiers" as an open question and pointed to the alpha/beta/GA model in Kubernetes. This SEP answers that question for extensions.
+
+## Specification
+
+### Stages
+
+| Stage | Location | Protocol changes | Changes approved by | Entry | What implementers can expect |
+| - | - | - | - | - | - |
+| **Experimental** | `specification/experimental/`, or an `experimental-ext-` repository | Any change, at any time, without notice | Extension Maintainer | An Extension Maintainer adds it, or any Maintainer creates an `experimental-ext-` repository | Nothing. The design may change or disappear. |
+| **Beta** | `specification/beta/` | Any change, with breaking changes expected to be rare | Extension Maintainer | Extensions Track SEP | Real usage is welcome. Breaking changes are documented. |
+| **Stable** | `specification/stable/` | Only with a new core protocol revision | Extension Maintainer | Second Extensions Track SEP | Behavior is fixed within a protocol revision. |
+| **Core** | `specification/archived/` | As for the core specification | Core Maintainers | Standards Track SEP | As for the core specification. |
+
+Locations are paths inside an `ext-` repository. See [Repositories and directories](#repositories-and-directories).
+
+```mermaid theme={null}
+flowchart LR
+ Exp["Experimental specification/experimental/"]
+ Beta["Beta specification/beta/"]
+ Stable["Stable specification/stable/"]
+ Core["Core specification (extension archived)"]
+
+ Exp -->|"Extensions Track SEP"| Beta
+ Beta -->|"Extensions Track SEP"| Stable
+ Beta -->|"Standards Track SEP"| Core
+ Stable -->|"Standards Track SEP"| Core
+```
+
+An extension MUST NOT skip Beta, unless the Core Maintainers waive the requirement by a recorded vote. Extensions that are official when this SEP is finalized are classified in [Transition](#transition).
+
+### Roles
+
+An **Extension Maintainer** is a maintainer of the extension's repository who is listed in that repository's `MAINTAINERS.md`, as `ext-tasks` already does. As SEP-2133 provides for repository maintainers, the Core Maintainers appoint Extension Maintainers, who are normally the
+leads of the associated Working Group, or the facilitators of the associated Interest Group. Every extension MUST have at least one Extension Maintainer.
+
+"Extension Maintainer approval" means a pull request approved by at least one Extension Maintainer who is not its author. Extension Maintainers SHOULD coordinate changes through the associated Working Group or Interest Group, following its [decision-making process](https://modelcontextprotocol.io/community/working-interest-groups.md#decision-making-process).
+
+The Core Maintainers keep the authority SEP-2133 gives them over every extension, including the ability to modify, deprecate, archive or remove it. Lead Maintainers retain veto authority over each Core Maintainer decision in this SEP, per the
+[governance roles](https://modelcontextprotocol.io/community/governance.md#roles).
+
+### Repositories and directories
+
+An official extension lives in an `ext-` repository, which MAY group related extensions as SEP-2133 allows. The extensions in one repository MAY be at different stages. The repository name does not show a stage, and does not change when a stage changes.
+
+Inside the repository, the stage is the directory that holds the extension's specification. For example (the extension names are illustrative):
+
+```
+ext-tasks/
+ specification/
+ experimental/
+ partial-results.md
+ beta/
+ steering.md
+ stable/
+ tasks/
+ 2026-07-28/
+ draft/
+ archived/
+```
+
+* Each extension's specification MUST be at `specification//`, where `` is `experimental`, `beta` or `stable`, and `` is a file or a directory. An extension MUST NOT appear under more than one stage directory.
+* The stage directory MUST match the extension's stage, and is the only required marker of it. The layout below `` is for the Extension Maintainers to decide, except as [Stable](#stable) requires for revisions.
+* A stage change is a move from one stage directory to another, or to `specification/archived/`. An Extension Maintainer opens a pull request that makes the move and links the SEP that the change requires, if any, and a Core Maintainer approves it. This is the only change to an extension repository that needs Core Maintainer approval.
+* An Extension Maintainer MAY add a new extension under `specification/experimental/` with Extension Maintainer approval only.
+* GitHub does not redirect a moved path. The Extension Maintainers update the links that a move breaks.
+* Schemas, SDK packages, examples and other supporting files MAY live elsewhere in the repository. Where they belong to one extension, they SHOULD say which.
+* `specification/archived/` holds extensions that have been promoted to Core or have ended. See [Core](#core) and [Ending an extension](#ending-an-extension).
+
+**Experimental repositories.** The `experimental-ext-` repositories that SEP-2133 defines remain. Any Maintainer MAY create one. Everything in it is Experimental, so it needs no stage directories. An extension in an experimental repository enters Beta by moving into an `ext-` repository, under `specification/beta/`. That repository is an existing one for the area, or a new one that the Core Maintainers create. The Core Maintainers MAY create it by renaming the experimental repository, as they did for `ext-tasks` and `ext-skills`.
+
+The following apply at every stage:
+
+* Every extension MUST stay associated with a Working Group or Interest Group, as SEP-2133 requires.
+* The licensing, contributor license grant, trademark and antitrust terms of SEP-2133 apply.
+* Each extension MUST be listed on the extensions page of the MCP website with its current stage, and a Beta extension with its intended destination.
+
+SDKs keep the autonomy SEP-2133 gives them. Extensions stay disabled by default and require explicit opt-in, at every stage.
+
+### Experimental
+
+An Experimental extension is a prototype. An Extension Maintainer MAY add one under `specification/experimental/` in an existing `ext-` repository, and any Maintainer MAY create an `experimental-ext-` repository. Either can happen before or after a SEP is drafted.
+
+* Extension Maintainers MAY merge any change, including breaking changes, without notice, deprecation or Core Maintainer review.
+* Implementers MUST NOT expect two revisions of the extension to be compatible. They SHOULD pin to a tag or commit.
+
+Core Maintainers retain the ability to archive an Experimental extension, or an experimental repository, at any time.
+
+### Beta
+
+A Beta extension is one the Core Maintainers are willing to have implementers try. The goal is real usage: implementers learn what needs to change, and the design iterates.
+
+**Entry.** An Extension Maintainer, or the Working Group, submits an Extensions Track SEP under SEP-2133 and the [SEP guidelines](https://modelcontextprotocol.io/community/sep-guidelines.md). It is reviewed like a Standards Track SEP, and SEP-2133 already requires it to identify the
+Working Group and Extension Maintainers and to have a reference implementation in an official SDK. When the SEP is accepted, the extension moves to `specification/beta/`, as [Repositories and directories](#repositories-and-directories) describes.
+
+**Intended destination.** The Beta SEP SHOULD state whether the extension is intended to become Stable or to be promoted to Core. The destination is a signal to implementers, not a commitment. Extension Maintainers MAY change it during Beta, and the SEP that moves the extension out of Beta decides. A change of intended destination SHOULD be announced like a breaking change.
+
+**Iteration.** After entry, Extension Maintainers approve changes without further Core Maintainer review.
+
+* Extensions SHOULD prefer additive changes, such as new optional fields or capability flags, over breaking changes.
+* Breaking changes are allowed but SHOULD be infrequent and SHOULD be batched.
+* Every breaking change MUST appear in a changelog with the revision that introduces it.
+* Extension Maintainers SHOULD announce a breaking change in the Working Group or Interest Group channel before merging it.
+* Extension Maintainers SHOULD maintain a public list of known implementations and the feedback received from them. This list is the evidence for the next stage.
+
+**Exit.** A Beta extension advances to Stable or Core, or is archived.
+
+### Stable
+
+A Stable extension is a released, maintained part of the MCP ecosystem that lives outside the core specification.
+
+**Entry.** An Extension Maintainer, or the Working Group, submits a second Extensions Track SEP. It follows the same review and acceptance process as a Standards Track SEP. The SEP MUST:
+
+* Link the Beta SEP and the extension's location, and show that the extension has been in real use, through the known-implementations list.
+* Show two independent implementations, at least one client-side and one server-side, that interoperate.
+* Carry a conformance scenario that meets the requirements of [SEP-2484](https://modelcontextprotocol.io/seps/2484-conformance-tests-required-for-final-seps.md) for a Standards Track SEP, unless the extension has no observable protocol behavior. This SEP extends SEP-2484 to Extensions Track SEPs that move an
+ extension to Stable.
+
+When the SEP reaches Final, the extension moves to `specification/stable/`, and the Extension Maintainers publish the first Stable revision.
+
+**Revisions.** A Stable extension is published as revisions keyed to core protocol revisions, for example a `specification/stable//2026-07-28/` snapshot beside a `specification/stable//draft/` directory.
+
+* A published revision is immutable.
+* The extension MAY change only by publishing a new revision together with, or after, a new core protocol revision is released as Current. Proposed changes accumulate in `draft/` and are visible to implementers before they take effect.
+* Extension Maintainer approval is sufficient for a new revision. The Core Maintainers do not review it.
+* Editorial fixes that do not change the requirements on any implementation MAY be made to a published revision at any time.
+
+**Compatibility.** See [Identifiers and compatibility](#identifiers-and-compatibility).
+
+**Exit.** A Stable extension may be promoted to Core or deprecated.
+
+### Core
+
+An extension that belongs in the core protocol is promoted by a Standards Track SEP, reviewed like any other. The proposal MAY come from a Beta or a Stable extension. The SEP MUST cite the extension's repository and location.
+
+The feature becomes part of the core protocol in a specific core protocol revision R, for example `2027-01-01`. Once R is released, the following rules apply:
+
+* **R or later.** For a request that declares R or later, the feature is core behavior. It applies whether or not the extension identifier is advertised, so a server responding under R or later does not need to advertise the extension or respond with it.
+* **Earlier than R.** For a request that declares an earlier revision, the extension applies as defined by its final revision. A client that still supports earlier revisions SHOULD keep advertising the extension identifier, so that a server that does not yet support R can fall
+ back to the extension behavior.
+* **When to stop.** A peer stops advertising the extension when it no longer supports any revision earlier than R. There is no separate sunset period.
+* **Differences.** The core behavior MAY differ from the extension. The SEP MUST define the differences, so that each protocol revision has one defined behavior.
+
+When the SEP reaches Final, the specification text lands in the core draft. The extension keeps its current stage until R is released as Current. The extension then moves to `specification/archived/`, with a notice at the top that points to the core specification section and the SEP. The archived copy keeps the extension's final revision, which remains the definition for earlier protocol revisions. From that point every change is a core specification change. Other extensions in the same repository are not affected.
+
+### Ending an extension
+
+* **Withdrawal or inactivity.** An Extension Maintainer MAY withdraw an Experimental or Beta extension, and it then moves to `specification/archived/`. The Core Maintainers MAY archive an Experimental or Beta extension that has had no merged change and no Working Group or Interest Group activity for six months.
+* **Deprecation.** A Stable extension is deprecated by an Extensions Track SEP, with the requirements, minimum window and Tier 1 SDK obligations that SEP-2596 sets for a core feature. It stays under `specification/stable/` while deprecated, and moves to `specification/archived/` when it is removed.
+
+An archived extension keeps its name, identifier and history, with a notice at the top that says why it was archived. The Core Maintainers archive a repository when every extension in it is archived, and archive an `experimental-ext-` repository as a whole.
+
+### Identifiers and compatibility
+
+This section replaces the rule in SEP-2133 that every breaking change MUST use a new identifier.
+
+* An extension's identifier is fixed when the extension is created and does not change when its stage changes.
+* **Experimental and Beta.** Extensions SHOULD prefer additive changes, such as new optional fields or capability flags in the settings object, over breaking changes. Breaking changes keep the same identifier, and the identifier carries no compatibility promise between revisions.
+ An extension that makes a breaking change SHOULD add or increment a `revision` string in its settings object so that peers can detect a mismatch. An absent `revision` means the initial revision. A peer that receives a `revision` it does not know SHOULD NOT enable the extension.
+* **Stable.** Breaking changes appear only in a new revision, keyed to a core protocol revision. The behavior of the extension for a peer pair is the behavior defined for the protocol revision they negotiate. A revision MUST NOT change the behavior already defined for an earlier
+ protocol revision. No new identifier is needed. A new identifier is used only when the old and new behavior must coexist under one protocol revision.
+* An extension specification MUST state which protocol revisions each of its revisions applies to.
+* Implementers of all stages SHOULD treat extension data received from a peer as untrusted, as SEP-2133 requires.
+
+### Transition
+
+When this SEP reaches Final:
+
+* `docs/extensions/overview.mdx` and the Extensions Track description in `docs/community/sep-guidelines.mdx` are updated to match this SEP.
+* The extensions page lists each extension with its stage.
+* The extensions in existing repositories are classified as follows. No repository is renamed. The Extension Maintainers of each `ext-` repository move its specification into the stage directory shown, and a Core Maintainer approves the move.
+
+| Repository | Stage at Final | Specification moves to |
+| - | - | - |
+| `ext-apps`, `ext-auth` | Stable | `specification/stable/` |
+| `ext-skills`, `ext-tasks` | Beta | `specification/beta/` |
+| `ext-server-card` | Beta | `specification/beta/` |
+| `experimental-ext-interceptors`, `experimental-ext-variants`, `experimental-ext-triggers-events`, `experimental-ext-tool-annotations` | Experimental | No change |
+
+* The classified extensions need no new SEP. Their existing SEPs, including SEP-2127 for `ext-server-card`, count as the SEP for the stage assigned, and they keep their identifiers and wire behavior. Their existing SEPs do not state an intended destination, so the Extension Maintainers of each Beta extension record one on the extensions page.
+* Extensions classified as Stable follow the revision rules from Final. Their next revision is keyed to the next core protocol revision, and their existing published specifications keep their content.
+* Dated snapshots and `draft/` directories that sit directly under `specification/` today, as in `ext-apps` and `ext-tasks`, move under the extension's own directory, for example `specification/beta/tasks/2026-07-28/`.
+* `ext-auth` keeps hosting several extensions, and each is classified as Stable. Its `specification/stable/` and `specification/draft/` directories hold different extensions today. Both extensions move under `specification/stable/`, and each gets its own `draft/` directory.
+* `ext-skills` publishes `specification/stable/` today, where "stable" means the released revision. Its specification moves to `specification/beta/`.
+* An `experimental-ext-` repository that hosts several Experimental extensions, such as `experimental-ext-tool-annotations`, is unchanged. An extension in it that requests Beta moves to an `ext-` repository, and the others stay.
+
+## Rationale
+
+**Why put the stage in a directory, and not in the repository name?** An earlier draft of this SEP used the repository name (`experimental-ext-`, `beta-ext-`, `ext-`). That allows one stage per repository, but one area often holds work at several stages. The Tasks and Events Working Group plans to stabilize the current Tasks extension while steering and intermediate results incubate beside it ([agents-wg#29](https://github.com/modelcontextprotocol/agents-wg/pull/29)), and `ext-auth` already keeps one extension under `specification/stable/` and another under `specification/draft/`. With stages in repository names, each of those would need a second repository with its own maintainers file, issues and packages. A directory lets them share one. It also avoids renames, which GitHub redirects but which break package names and module paths at every stage change.
+
+The directory is still visible in every link to the specification, which a README banner or front-matter label would not be. There are two costs. GitHub does not redirect a moved path, so links to the old path on the default branch break. Links to a tag or commit do not break, and the extensions page on the MCP website is the stable entry point. A move also needs only write access, where a rename needs administrator access. This SEP therefore requires a Core Maintainer to approve the move.
+
+**Why does Beta need a SEP, but iteration inside Beta does not?** Beta is the first stage where the project's name stands behind an extension, so it gets the full review that SEP-2133 already requires for official extensions. Iteration after that follows the reasoning in
+SEP-2133: routing every change through Core Maintainer review would bottleneck extensions on a process that already takes months.
+
+**Why a second SEP for Stable?** Stable is a stronger promise than Beta: behavior is fixed within a protocol revision. A second review lets the Core Maintainers judge the evidence from Beta (real usage, independent implementations and conformance) before making that promise.
+
+**Why can a Stable extension change only with a core protocol revision?** Implementers need known dates for behavior changes. Because every request declares its protocol revision, tying extension revisions to core revisions gives a change a place to take effect without breaking
+peers on an earlier revision. It also matches current practice: `ext-tasks` snapshots its schema by core revision, and `ext-skills` pins its stable specification to `2026-07-28`.
+
+**Why is Beta required before Stable?** The purpose of Beta is real usage before the project commits to a design. The Stable evidence is easier to gather during Beta, and a Beta extension is cheap to change if the evidence shows a problem. The Core Maintainers can still waive the
+requirement.
+
+**Why does a Beta extension state an intended destination?** The two exits from Beta set different expectations. An extension heading for Core will later be defined by core protocol revisions and its identifier will stop being advertised, while one heading for Stable stays an extension. Implementers deciding how deeply to adopt a Beta extension need to know which to expect. The destination is not binding, because Beta exists to gather the evidence that decides it.
+
+**Why does the extension stay advertised after promotion to Core?** Protocol revisions are negotiated per request, so a client cannot know in advance whether a server supports R. Advertising the extension lets the same client work with servers on either side of R, and the core
+behavior needs no negotiation once both sides are on R.
+
+**Alternatives considered.**
+
+* *Put the stage in the repository name (`experimental-ext-`, `beta-ext-`, `ext-`).* It limits a repository to one stage, so an area with work at several stages needs several repositories, and it renames the repository at every stage change. See the first question above.
+* *Put the extension first and the stage second, for example `tasks/beta/spec.md`.* It keeps an extension's path prefix fixed across stages, but a reader cannot list everything at one stage, and the stage sits deeper in every link.
+* *Beta by Core Maintainer vote instead of a SEP.* Lighter, but it creates a second, unwritten approval path for official extensions and leaves no written record of the design.
+* *Give Experimental and Beta extensions a distinct identifier, for example `io.modelcontextprotocol.experimental/`.* It makes the stage visible on the wire, but every stage change would force implementers to change code and identifiers. The `revision` setting gives most of
+ the benefit at less cost.
+* *Require a new identifier for every Stable breaking change (SEP-2133 as written).* It leaves old and new behavior coexisting indefinitely and forces both to be implemented. Keying behavior to the negotiated protocol revision reuses a mechanism the protocol already has.
+
+**Prior art.** Kubernetes moves features through [alpha, beta and GA stages](https://kubernetes.io/docs/reference/command-line-tools-reference/feature-gates/) with different stability promises and
+[deprecation windows](https://kubernetes.io/docs/reference/using-api/deprecation-policy/), which [SEP-2596](https://modelcontextprotocol.io/seps/2596-spec-feature-lifecycle-and-deprecation.md) already cites. OpenTelemetry Collector components carry
+[development, alpha, beta and stable stability levels](https://github.com/open-telemetry/opentelemetry-collector/blob/main/docs/component-stability.md). The Node.js [Stability Index](https://nodejs.org/api/documentation.html#stability-index) marks APIs as experimental or stable,
+among other levels.
+
+## Backward Compatibility
+
+This SEP changes process only, and changes no message on the wire.
+
+* It replaces the identifier rule and the creation, iteration and promotion steps of SEP-2133 with the rules above.
+* No repository is renamed, so repository URLs, package names and module paths do not change.
+* Existing Experimental repositories are unchanged.
+* `ext-skills`, `ext-tasks` and `ext-server-card` are classified as Beta. Their identifiers and wire behavior do not change. Their specifications move to `specification/beta/`, which breaks links to the old paths on the default branch.
+* `ext-apps` and `ext-auth` are classified as Stable, and their specifications move to `specification/stable/`. From Final, changes to their published specifications wait for a core protocol revision.
+
+## Security Implications
+
+Experimental and Beta extensions iterate without Core Maintainer review, so an insecure design can be implemented before anyone with security expertise reads it. The controls are:
+
+* Extensions stay disabled by default at every stage, so an implementer opts in deliberately.
+* Beta entry requires an Extensions Track SEP, including its Security Implications section, and Stable entry requires a second full SEP review.
+* An extension enters `specification/beta/` or `specification/stable/` only through a pull request that a Core Maintainer approves, so an extension cannot show a stage that no SEP has granted.
+* Stable changes take effect only with a core protocol revision, and are visible in `draft/` beforehand.
+* Core Maintainers keep the authority to archive an extension at any stage, for example when a vulnerability is reported.
+
+Allowing breaking changes under one identifier at Experimental and Beta stages means two implementations built against different revisions can negotiate the extension and then misparse each other's data. Implementations MUST validate extension data (SEP-2133), and the `revision`
+setting, where present, lets a peer refuse a revision it does not know.
+
+## Reference Implementation
+
+This is a Process SEP and has no protocol implementation. On reaching Final it lands the documentation changes and directory moves listed in [Transition](#transition).
diff --git a/content/support/10310342-how-do-i-log-out-of-all-active-sessions.md b/content/support/10310342-how-do-i-log-out-of-all-active-sessions.md
index beff798e31..3d6933884c 100644
--- a/content/support/10310342-how-do-i-log-out-of-all-active-sessions.md
+++ b/content/support/10310342-how-do-i-log-out-of-all-active-sessions.md
@@ -46,7 +46,7 @@ Logging out of all active sessions also logs you out of Claude Code. To log out
If you used your Claude account to authenticate into Claude Code, you can see and log out of those sign-ins in **Settings > Account**, where they're listed with your other sessions. If they aren't listed there, manage your authorization tokens in **Settings > Claude Code**. To remove a token and log out of Claude Code, click the trash can icon.
-
+
## Unable to access your account?
diff --git a/content/support/10504844-manage-user-feedback-settings-on-team-and-enterprise-plans.md b/content/support/10504844-manage-user-feedback-settings-on-team-and-enterprise-plans.md
index 9aeadb16cc..ee4a40f359 100644
--- a/content/support/10504844-manage-user-feedback-settings-on-team-and-enterprise-plans.md
+++ b/content/support/10504844-manage-user-feedback-settings-on-team-and-enterprise-plans.md
@@ -6,6 +6,6 @@ As a Primary Owner or Owner of a Team or Enterprise plan, you can manage the abi
2. Use the toggle to change the **Rate chats** setting for your organization:
-
+
More information on how Anthropic collects, uses, and stores feedback data can be found in our Privacy Center: **[How long do you store my organization’s data?](https://privacy.claude.com/en/articles/7996866-how-long-do-you-store-my-organization-s-data)**
\ No newline at end of file
diff --git a/content/support/10593882-share-and-unshare-chats.md b/content/support/10593882-share-and-unshare-chats.md
index 7243e74b06..b809514200 100644
--- a/content/support/10593882-share-and-unshare-chats.md
+++ b/content/support/10593882-share-and-unshare-chats.md
@@ -38,12 +38,12 @@ To unshare a chat:
Users on free, Pro, or Max plans can review a log of shared chats by navigating to **[Settings > Privacy](https://claude.ai/settings/data-privacy-controls)**. Find the **Privacy settings** section and click “Manage” next to **Shared chats:**
-
+
This will open a **Shared chats** modal listing the title, date shared, and link to each chat, allowing you to easily review and access all your previously-shared content. From here, you also have the option to click “Unshare” next to each listed chat to revoke access to the last snapshot you shared:
-
+
If you don’t have any shared chat snapshots, the **Shared chats** modal will show “No shared content found”:
-
\ No newline at end of file
+
\ No newline at end of file
diff --git a/content/support/10949351-getting-started-with-local-mcp-servers-on-claude-desktop.md b/content/support/10949351-getting-started-with-local-mcp-servers-on-claude-desktop.md
index 1b065100b8..9aafd5b17b 100644
--- a/content/support/10949351-getting-started-with-local-mcp-servers-on-claude-desktop.md
+++ b/content/support/10949351-getting-started-with-local-mcp-servers-on-claude-desktop.md
@@ -48,7 +48,7 @@ for specific instructions.
Custom desktop extensions uploads allow Team and Enterprise plans to leverage organization-specific workflows that aren’t available in the public directory. After creating a custom desktop extension, Owners and Primary Owners can navigate to **Settings > Desktop app**, select "Manage" next to **Extensions** (or **Settings > Extensions** in the older Settings layout), and click "Advanced settings" to access the **Extension Developer** section:
-
+
Click “Install Extension…” and select the .mcpb file. Follow the prompts to install and configure your custom desktop extension. For more in-depth information, please refer to our [desktop extension developer documentation](https://github.com/anthropics/mcpb).
diff --git a/content/support/11101966-use-voice-mode.md b/content/support/11101966-use-voice-mode.md
index 0b058b879b..9bfd4751f8 100644
--- a/content/support/11101966-use-voice-mode.md
+++ b/content/support/11101966-use-voice-mode.md
@@ -24,7 +24,7 @@ Voice mode transforms how you interact with Claude by:
2. Tap the sound wave symbol in the lower right corner of the chat window to activate voice mode:
-
+
3. Start talking and see your prompt automatically populate in the chat input.
@@ -32,7 +32,7 @@ Voice mode transforms how you interact with Claude by:
5. Claude will remain in voice mode until you click the “Stop” button in the lower right corner of the chat window:
-
+
### On mobile (iOS and Android)
@@ -40,7 +40,7 @@ Voice mode transforms how you interact with Claude by:
2. Tap the voice mode icon (sound wave symbol next to the microphone icon) in the text input field:
-
+
3. Choose a voice to personalize your experience.
@@ -78,7 +78,7 @@ To change the voice later:
- **On mobile:** Click the settings button in the bottom left corner while chatting with Claude in voice mode, then tap your preferred voice and pace:
-
+
## Choose a model
diff --git a/content/support/11725453-set-up-the-claude-lti-in-canvas-by-instructure.md b/content/support/11725453-set-up-the-claude-lti-in-canvas-by-instructure.md
index b6e3c35e73..f423b586e8 100644
--- a/content/support/11725453-set-up-the-claude-lti-in-canvas-by-instructure.md
+++ b/content/support/11725453-set-up-the-claude-lti-in-canvas-by-instructure.md
@@ -44,7 +44,7 @@ This article provides information on how to enable the Claude LTI integration in
5. Click "Install" and refresh the course page.
-
+
## Turn on the Claude LTI Integration in Claude for Education organization settings
diff --git a/content/support/11817273-use-claude-s-chat-search-and-memory-to-build-on-previous-context.md b/content/support/11817273-use-claude-s-chat-search-and-memory-to-build-on-previous-context.md
index 721e035570..8b479100b0 100644
--- a/content/support/11817273-use-claude-s-chat-search-and-memory-to-build-on-previous-context.md
+++ b/content/support/11817273-use-claude-s-chat-search-and-memory-to-build-on-previous-context.md
@@ -80,7 +80,7 @@ To run a single chat or Cowork task without memory, open a new chat, click the
You can toggle Claude's memory on by navigating to **Settings > Your Claude** and turning on **Memory from chats** (or **Settings > Memory** and **Generate memory from chats** in the older Settings layout):
-
+
If you want to disable Claude’s memory, click the toggle and you'll see two options:
@@ -276,7 +276,7 @@ When Claude searches your previous chats, you will see this reflected in your cu
Yes, navigate to **Settings > Your Claude** (or **Settings > Capabilities** in the older Settings layout) and find the **Memory** section. Switch the toggle next to “Search and reference chats” off:
-
+
### Can I exclude a specific past chat from searches?
@@ -284,7 +284,7 @@ Incognito chats are available to all Claude users (free, Pro, Max, Team, and Ent
When starting a new chat with Claude outside of a project, you'll see a ghost icon in the upper right corner of your screen:
-
+
Clicking the ghost icon will open an incognito chat, creating a temporary conversation that isn’t saved to your chat history. Claude won’t pull information from incognito chats when searching previous conversations.
@@ -316,7 +316,7 @@ Each project has its own separate memory space and dedicated project summary, so
You can toggle Claude's memory on by navigating to **Settings > Your Claude** (or **Settings > Capabilities** in the older Settings layout):
-
+
If you want to disable Claude’s memory, click the toggle to see two options:
diff --git a/content/support/11818288-why-am-i-being-asked-to-verify-my-payment-method.md b/content/support/11818288-why-am-i-being-asked-to-verify-my-payment-method.md
index 4fa380efc0..176f6a1cb4 100644
--- a/content/support/11818288-why-am-i-being-asked-to-verify-my-payment-method.md
+++ b/content/support/11818288-why-am-i-being-asked-to-verify-my-payment-method.md
@@ -2,7 +2,7 @@
If you see the following pop-up when you log in to your Claude account, you’ll need to click the “Verify now” button to verify your payment method:
-
+
## What happens if I click “Remind me later?”
diff --git a/content/support/11869629-use-claude-with-android-apps.md b/content/support/11869629-use-claude-with-android-apps.md
index d829c2e95d..136d05ee1c 100644
--- a/content/support/11869629-use-claude-with-android-apps.md
+++ b/content/support/11869629-use-claude-with-android-apps.md
@@ -222,7 +222,7 @@ Permission requirements vary by feature:
For features requiring permissions (like location or calendar access), Claude will request permission contextually with clear explanations of why the access is needed. You’ll be prompted to approve the action with three options: Allow once, Always allow, or Don't allow.
-
+
These permissions can be managed at any time in your device settings by going to Settings > Apps > Claude > Permissions. Click into each permission listed under **Allowed** and **Not allowed** to make changes. You can toggle between “Allow only while using the app” or “Ask every time” to change Claude’s access, or remove permissions by choosing “Don’t allow.” Claude will only request permissions if needed for specific features, and you can always choose to decline while still using other capabilities.
diff --git a/content/support/12005970-manage-usage-credits-for-team-and-seat-based-enterprise-plans.md b/content/support/12005970-manage-usage-credits-for-team-and-seat-based-enterprise-plans.md
index 45b1194b40..672839e562 100644
--- a/content/support/12005970-manage-usage-credits-for-team-and-seat-based-enterprise-plans.md
+++ b/content/support/12005970-manage-usage-credits-for-team-and-seat-based-enterprise-plans.md
@@ -70,7 +70,7 @@ After navigating to **[Organization settings > Usage](https://claude.ai/admin-se
The **Usage and spend limits** section will show the current limit (if any) or **Unlimited**. Clicking on "Adjust limit" opens a modal where you can either input an amount and click "Set spend limit," or click "Set to unlimited" to remove the organization-wide monthly spend limit.
-
+
Changes to your organization’s overall spend limit go into effect immediately.
@@ -78,11 +78,11 @@ Changes to your organization’s overall spend limit go into effect immediately.
Owners and Primary Owners on **seat-based Enterprise plans only** can set spend limits that apply to all users within a specific seat tier.
-
+
Select the "By group" tab to see **Standard seats** and **Premium seats** groups. Click the "..." icon next to the current limit, then "Edit limit." This opens a modal where you can either select "Set dollar amount" and input an amount, or click "Unlimited" to remove the limit for that seat type. Click "Set limit" to save your changes.
-
+
---
@@ -90,11 +90,11 @@ Select the "By group" tab to see **Standard seats** and **Premium seats** groups
Owners and Primary Owners can also set individual monthly spend limits for each member by finding **Spend limits by user** and clicking the "..." button next to the user, then "Edit limit."
-
+
Enter the amount and click "Set limit." Alternatively, selecting "Set to unlimited" will remove that member's monthly spend limit (they will still be subject to any organization or seat-level spend limits).
-
+
This allows owners fine control over usage credits, so you can set limits for different members based on their roles or individual needs. Once a user reaches their defined spend limit, this will automatically pause their usage credits until the end of the month. They will need to wait for their usage limits to reset before using Claude again.
diff --git a/content/support/12012173-get-started-with-claude-in-chrome.md b/content/support/12012173-get-started-with-claude-in-chrome.md
index b2c745b62b..a523a0c398 100644
--- a/content/support/12012173-get-started-with-claude-in-chrome.md
+++ b/content/support/12012173-get-started-with-claude-in-chrome.md
@@ -40,7 +40,7 @@ Follow these steps to connect Claude in Chrome in your desktop app:
4. Toggle the connector on, then download and install the extension if you haven’t already.
-
+
Completing these steps will add Claude in Chrome to the “Connectors” drop-down on your chats with Claude. This is disabled by default, so you’ll need to enable it manually for each conversation.
diff --git a/content/support/12083917-change-your-team-plan-from-monthly-to-annual-billing.md b/content/support/12083917-change-your-team-plan-from-monthly-to-annual-billing.md
index f108fd319f..9139f7a3b0 100644
--- a/content/support/12083917-change-your-team-plan-from-monthly-to-annual-billing.md
+++ b/content/support/12083917-change-your-team-plan-from-monthly-to-annual-billing.md
@@ -8,11 +8,11 @@ Owners and Primary Owners of Team plans with monthly subscriptions can switch fr
3. Or from /upgrade, click the “Switch to Annual plan” button:
-
+
4. The confirmation screen will display the total cost for your upgrade from monthly to annual billing:
-
+
5. Click “Confirm subscription.”
diff --git a/content/support/12111783-create-and-edit-files-with-claude.md b/content/support/12111783-create-and-edit-files-with-claude.md
index b7a0461e8b..3f63fd7b2b 100644
--- a/content/support/12111783-create-and-edit-files-with-claude.md
+++ b/content/support/12111783-create-and-edit-files-with-claude.md
@@ -48,7 +48,7 @@ These capabilities make it easy to produce professional documents by simply chat
To give Claude access to external data sources, toggle **Allow network egress** on:
-
+
### Enabling on Claude Mobile
@@ -66,11 +66,11 @@ Team and Enterprise organization owners can control network access settings in *
- **Allow network egress to package managers and specific domains:** Claude can access package managers plus additional domains you specify. Add domains individually to whitelist specific resources your organization needs:
-
+
**All domains:** Claude has full internet access except for domains on Anthropic's legal blocklist. While this provides maximum flexibility for file creation and analysis tasks, it’s also the riskiest option. Please review the **[security considerations below](#h_0ee9d698a1)** before enabling “All domains”:
-
+
---
diff --git a/content/support/12157520-claude-code-usage-analytics.md b/content/support/12157520-claude-code-usage-analytics.md
index eb4f8223f8..c470ca8a46 100644
--- a/content/support/12157520-claude-code-usage-analytics.md
+++ b/content/support/12157520-claude-code-usage-analytics.md
@@ -46,7 +46,7 @@ The **Usage** tab displays the following metrics for your organization. Data on
- **Top commands**: The Claude Code commands used most often across your organization.
-
+
### User-level metrics
diff --git a/content/support/12260368-use-incognito-chats.md b/content/support/12260368-use-incognito-chats.md
index a4d55718f5..a4de294958 100644
--- a/content/support/12260368-use-incognito-chats.md
+++ b/content/support/12260368-use-incognito-chats.md
@@ -34,7 +34,7 @@ These differ from regular chats in several ways:
When starting a new chat with Claude outside of a project, you'll see a ghost icon in the upper right corner of your screen:
-
+
1. Click the ghost icon to enable incognito mode.
diff --git a/content/support/12293051-use-claude-in-xcode.md b/content/support/12293051-use-claude-in-xcode.md
index 7d408fb78b..c88d2e046c 100644
--- a/content/support/12293051-use-claude-in-xcode.md
+++ b/content/support/12293051-use-claude-in-xcode.md
@@ -34,7 +34,7 @@ To start using Claude in Xcode:
3. Log in with your Claude account.
-
+
## Usage limits
diff --git a/content/support/12429409-manage-usage-credits-for-paid-claude-plans.md b/content/support/12429409-manage-usage-credits-for-paid-claude-plans.md
index f20c018938..5be865bbfa 100644
--- a/content/support/12429409-manage-usage-credits-for-paid-claude-plans.md
+++ b/content/support/12429409-manage-usage-credits-for-paid-claude-plans.md
@@ -50,7 +50,7 @@ To enable usage credits on your paid Claude plan:
8. You can also enable auto-reload to automatically make a purchase when your balance falls below a threshold you set:
-
+
---
diff --git a/content/support/12466728-troubleshoot-claude-error-messages.md b/content/support/12466728-troubleshoot-claude-error-messages.md
index 9067262be4..f88de03cc6 100644
--- a/content/support/12466728-troubleshoot-claude-error-messages.md
+++ b/content/support/12466728-troubleshoot-claude-error-messages.md
@@ -60,4 +60,4 @@ Capacity issues will not appear on our status page because they represent normal
Service incidents are disruptions where Claude is unavailable or significantly degraded for all or most users. These represent actual technical problems with our systems. To check for confirmed incidents, visit status.claude.com, where you'll find real-time updates on scope, impact, and resolution progress for any active incidents.
-
\ No newline at end of file
+
\ No newline at end of file
diff --git a/content/support/12512180-use-skills-in-claude.md b/content/support/12512180-use-skills-in-claude.md
index 17cde994fc..94ae4d185c 100644
--- a/content/support/12512180-use-skills-in-claude.md
+++ b/content/support/12512180-use-skills-in-claude.md
@@ -202,7 +202,7 @@ To remove a custom skill you've uploaded:
4. To delete the custom skill entirely, click the "..." button next to the toggle, then select "Delete":
- 
+ 
5. Click "Delete" in the confirmation prompt.
diff --git a/content/support/12592343-enabling-and-using-the-desktop-extension-allowlist.md b/content/support/12592343-enabling-and-using-the-desktop-extension-allowlist.md
index 697d8b3151..523dd48c7f 100644
--- a/content/support/12592343-enabling-and-using-the-desktop-extension-allowlist.md
+++ b/content/support/12592343-enabling-and-using-the-desktop-extension-allowlist.md
@@ -20,11 +20,11 @@ The desktop extension allowlist is disabled by default, so an organization Owner
4. Switch to the "Desktop" tab:
-
+
5. Toggle **Allowlist** on:
-
+
## What happens after enabling the allowlist?
@@ -42,7 +42,7 @@ Consider completing the allowlist setup during off-hours to minimize disruption
**Important:** The allowlist requires Claude Desktop version 0.13.91 or higher, so users should update the desktop app by clicking “Claude”, then either “Check for updates” or “Restart to update to Claude 0.13.91”:
-
+
## Managing allowed extensions
@@ -60,7 +60,7 @@ After enabling the allowlist, you can choose which extensions to allow:
If you want to remove an extension from the allowlist, click the “...” button and “Remove from allowlist.”
-
+
## Uploading custom extensions
diff --git a/content/support/12618689-use-claude-code-in-the-cloud.md b/content/support/12618689-use-claude-code-in-the-cloud.md
index af83ab8d01..4adec6a34b 100644
--- a/content/support/12618689-use-claude-code-in-the-cloud.md
+++ b/content/support/12618689-use-claude-code-in-the-cloud.md
@@ -10,7 +10,7 @@ This feature works with repositories you may not have on your local machine. You
Cloud sessions enable asynchronous development workflows. In a local session in your terminal or editor, you typically work synchronously: you make a request, wait for Claude to respond, review the changes, then make another request. Synchronous work like this gives you fine-grained control but requires your attention throughout the process. A cloud session handles this differently: you can assign a larger task, let Claude work independently, and return later to review the completed work.
-
+
You can also run multiple tasks in parallel. Since each task runs in its own isolated environment, you can have Claude working on several different issues or repositories simultaneously. Each task proceeds independently and creates its own pull request when complete. More than one task can work on the same repository at the same time.
@@ -20,13 +20,13 @@ You can also run multiple tasks in parallel. Since each task runs in its own iso
When you start a cloud session, Claude Code creates an isolated virtual machine for your work. Your GitHub repository is cloned into this environment, which comes pre-configured with common development tools and language ecosystems.
-
+
Claude prepares the environment by running any setup commands you've defined in your repository's configuration. This includes installing dependencies, setting up databases, or running other initialization steps your project needs. If your task requires network access, maybe to install packages or fetch data, you can configure the level of internet access the environment has.
Once the environment is ready, Claude begins working on your task. Claude reads your code, makes changes, writes tests, and runs commands to verify the work. You can monitor progress and provide guidance through the web interface if needed.
-
+
When Claude completes the task, it pushes the changes to a new branch in your GitHub repository. You receive a notification and can review the changes, then create a pull request directly from the interface. The pull request includes all of Claude's work, ready for your review and any additional changes you want to make.
diff --git a/content/support/12626668-use-quick-entry-with-claude-desktop-on-mac.md b/content/support/12626668-use-quick-entry-with-claude-desktop-on-mac.md
index d6f74a0a95..0ab4f1e5ca 100644
--- a/content/support/12626668-use-quick-entry-with-claude-desktop-on-mac.md
+++ b/content/support/12626668-use-quick-entry-with-claude-desktop-on-mac.md
@@ -40,7 +40,7 @@ When you first open the updated version of Claude Desktop, you'll see a prompt t
Once enabled, double-tapping Option will open a text box where you can type your message and start a new chat. You can also click "New chat" to see your five most recent conversations.
-
+
### Enable the voice shortcut (optional)
diff --git a/content/support/12883420-view-usage-analytics-for-team-and-enterprise-plans.md b/content/support/12883420-view-usage-analytics-for-team-and-enterprise-plans.md
index 5f822e4fa7..0307492b1b 100644
--- a/content/support/12883420-view-usage-analytics-for-team-and-enterprise-plans.md
+++ b/content/support/12883420-view-usage-analytics-for-team-and-enterprise-plans.md
@@ -22,7 +22,7 @@ This page includes the following analytics:
- Sessions in Cowork
-
+
### Who’s using Claude?
@@ -34,7 +34,7 @@ This page includes the following analytics:
Use the dropdown on the **Active members and assigned seats** chart to filter by product, including Claude Design.
-
+
### How are they using Claude?
@@ -48,9 +48,9 @@ Use the dropdown on the **Active members and assigned seats** chart to filter by
- How agentic is their work? (beta)
-
+
-
+
### What are the results?
@@ -66,7 +66,7 @@ Use the dropdown on the **Active members and assigned seats** chart to filter by
- Estimated time saved
-
+
### How much is Claude costing?
@@ -82,9 +82,9 @@ This section includes the following analytics:
- Spend by model (month-to-date, quarter-to-date, year-to-date, 1 year)
-
+
-
+
**Note:** For a view of how spend limits are affecting your organization, you can also check the **Blocked by a spend limit** section at the top of **[Organization settings > Usage](https://claude.ai/admin-settings/usage)**. **Blocked by a spend limit** is built for usage-based Enterprise plans. Orgs without usage-based seats only see how many members are blocked or near their limit right now. Learn more about **[monitoring usage and spend on Enterprise plans](https://support.claude.com/en/articles/11526368-how-am-i-billed-for-my-enterprise-plan#h_ae17ec8236)**.
@@ -162,7 +162,7 @@ Navigate to **[Analytics > Claude Chat](https://claude.ai/analytics/usage)** to
- Top members by chats
-
+
### Projects
@@ -174,7 +174,7 @@ Navigate to **[Analytics > Claude Chat](https://claude.ai/analytics/usage)** to
- Top members by project usage
-
+
### Artifacts
@@ -184,7 +184,7 @@ Navigate to **[Analytics > Claude Chat](https://claude.ai/analytics/usage)** to
- Top 10 users by artifacts generated (month-to-date, quarter-to-date, year-to-date, 1 year)
-
+
---
@@ -280,7 +280,7 @@ Navigate to **[Analytics > Cowork](https://claude.ai/analytics/cowork)** to view
- Daily, weekly, and monthly active Cowork users
-
+
**Note:** Cowork analytics are available alongside Chat and Claude Code data in the **[Analytics API](https://platform.claude.com/docs/en/manage-claude/analytics-api)**.
@@ -296,7 +296,7 @@ Navigate to **[Analytics > Surveys](https://claude.ai/analytics/surveys)** to as
On Enterprise plans with usage-based billing, when your admin turns on individual usage analytics, any member of the organization can see their own usage broken down by product, model, and skill, along with where they stand against any spend limits set for them. Individual usage analytics are available in **[Settings > Usage](https://claude.ai/settings/usage)**.
-
+
---
diff --git a/content/support/12902446-claude-in-chrome-permissions-guide.md b/content/support/12902446-claude-in-chrome-permissions-guide.md
index 4946db7c0c..a3c89c2e40 100644
--- a/content/support/12902446-claude-in-chrome-permissions-guide.md
+++ b/content/support/12902446-claude-in-chrome-permissions-guide.md
@@ -30,7 +30,7 @@ In "Manually approve," Claude checks with you before it acts. What that looks li
Claude creates a plan from your prompt, which you can approve before Claude starts. The plan specifies which websites you're allowing Claude to access, as well as the approach it will follow:
-
+
Note that Claude will only use the websites listed in the plan, so you’ll need to manually approve any additional access requests.
@@ -64,7 +64,7 @@ When you choose "Skip all approvals," Claude doesn't pause to ask, and nothing c
There are some websites on which Claude requires approval for every action. If you navigate to one of these sites, a **New permissions required** prompt will appear in the extension side panel, Claude Cowork, or Claude Code where Claude will ask for permission before accessing the page or taking any action.
-
+
### Permission options
diff --git a/content/support/12997503-team-plan-billing-faqs.md b/content/support/12997503-team-plan-billing-faqs.md
index f9f0405f3d..d125e826e8 100644
--- a/content/support/12997503-team-plan-billing-faqs.md
+++ b/content/support/12997503-team-plan-billing-faqs.md
@@ -18,7 +18,7 @@ Your organization's billing address determines where your invoices are sent. You
If you want to use a name other than the one tied to your payment method, an organization Owner should check the "Use a different name on invoices" box when adding or updating your payment method in **[Organization settings > Billing](https://claude.ai/admin-settings/billing)**:
-
+
## When will I be billed?
diff --git a/content/support/13132885-set-up-single-sign-on-sso.md b/content/support/13132885-set-up-single-sign-on-sso.md
index 930810bdb2..a9c0486e2c 100644
--- a/content/support/13132885-set-up-single-sign-on-sso.md
+++ b/content/support/13132885-set-up-single-sign-on-sso.md
@@ -42,7 +42,7 @@ You can verify multiple domains for a single organization, but all domains must
3. Enter the domain(s) you want to verify in the **Update organization email domains** modal and click the “+” button:
-
+
4. Click “Save” when you’re finished adding domains.
@@ -50,7 +50,7 @@ You can verify multiple domains for a single organization, but all domains must
6. Enter your domain in the text box and click “Continue”:
-
+
7. The setup screen displays a TXT record. **Copy the full Value using the copy button**—it begins with `anthropic-domain-verification-` and is longer than what's visible in the box. In your DNS provider, add a TXT record to your domain and **Value** set to the copied string. The domain must match exactly what you entered in the previous step, including any subdomains. Add it alongside any existing TXT records; don't replace them. The value is case-sensitive, so paste it exactly. Please refer to your DNS provider's documentation on this topic.
@@ -76,7 +76,7 @@ Clicking "Refresh" re-checks your DNS; it won't show Verified until the publishe
If the record is correct and propagated but the status still shows Pending, contact Support.
-
+
**Note:** Once your domain is verified, you'll see a **Restrict organization creation** toggle under **Security** on the Organization and access organization settings page. Enable this if you want to prevent users from creating new Claude or Console organizations—including personal accounts—using your verified domains.
@@ -116,7 +116,7 @@ For IdP-specific setup instructions, see:
You can now choose to toggle on **Require SSO for Console** and/or **Require SSO for Claude,** on the **Organization and access** page, under the **Authentication** section:
-
+
When SSO is required, users must use the “Continue with SSO” option to log in to their Claude/Console accounts. When SSO is not required, they will have the option to choose “Continue with SSO” or “Continue with email.”
diff --git a/content/support/13133195-set-up-jit-or-scim-provisioning.md b/content/support/13133195-set-up-jit-or-scim-provisioning.md
index 66a12853fd..9dbc827bef 100644
--- a/content/support/13133195-set-up-jit-or-scim-provisioning.md
+++ b/content/support/13133195-set-up-jit-or-scim-provisioning.md
@@ -40,7 +40,7 @@ Use this table to help decide which provisioning mode is right for your organiza
Both JIT and SCIM can be combined with **Enable group mappings** to control role or seat tier assignment based on IdP group membership. If you select either of these options for your provisioning mode, **Enable group mappings** will appear within the **User provisioning** section:
-
+
**Important:** Group mappings set a user’s role type and seat tier only. Users with the Custom role get their permissions from groups in Claude, and those groups sync from your IdP only when your provisioning mode is SCIM directory sync. With JIT, you need to create groups and add users to them manually in **[Organization settings > Groups](https://claude.ai/admin-settings/groups)**. If you map an IdP group to the Custom role under JIT without doing this, those users have no permissions when they log in. Learn more about **[managing groups on Enterprise plans](https://support.claude.com/en/articles/13799932)**.
@@ -136,7 +136,7 @@ Learn more about **[setting up role-based permissions on Enterprise plans](https
4. Toggle **Enable group mappings** on (if it’s not already):
- 
+ 
5. In the **Enable group mappings** section, click “Add” next to each role and select the corresponding group from your IdP in the dropdown.
@@ -188,7 +188,7 @@ Verify you have enough seats purchased and available to add members to your org.
4. **For SCIM:** Click "Sync" to prompt an immediate sync, or wait for the automatic sync cycle:
- 
+ 
### Users mapped to the Custom role can't access anything after logging in
diff --git a/content/support/13163631-configuring-session-security-settings.md b/content/support/13163631-configuring-session-security-settings.md
index 4ec57410a4..f7e1b371cb 100644
--- a/content/support/13163631-configuring-session-security-settings.md
+++ b/content/support/13163631-configuring-session-security-settings.md
@@ -18,7 +18,7 @@ Session duration controls allow Enterprise and Console Admins to set a maximum s
5. Confirm your selection by clicking “Enable.”
-
+
### For Console Admins
@@ -32,7 +32,7 @@ Session duration controls allow Enterprise and Console Admins to set a maximum s
5. Confirm your selection by clicking “Enable.”
-
+
### What happens after enabling shortened session length?
@@ -50,7 +50,7 @@ You can change the session duration at any time by selecting a new value from th
- Sessions scheduled to expire beyond the new duration will have their expiration shortened accordingly.
-
+
## Disabling session length settings
diff --git a/content/support/13189465-log-in-to-your-claude-account.md b/content/support/13189465-log-in-to-your-claude-account.md
index 3c09defbdc..6c1875edb2 100644
--- a/content/support/13189465-log-in-to-your-claude-account.md
+++ b/content/support/13189465-log-in-to-your-claude-account.md
@@ -2,7 +2,7 @@
When you open Claude on a web browser ([claude.ai](https://claude.ai)), the desktop app, or a mobile app, you will see two different options for logging in to your Claude account.
-
+
## Continue with Google
diff --git a/content/support/13325567-account-management-faqs.md b/content/support/13325567-account-management-faqs.md
index 93a0c384bc..69bea0146f 100644
--- a/content/support/13325567-account-management-faqs.md
+++ b/content/support/13325567-account-management-faqs.md
@@ -44,6 +44,6 @@ The email domain that was used to create your Team or Enterprise plan organizati
Owners can remove domains by opening up the same modal and clicking the trash can icon to the right of the domain:
-
+
While the account creator must use a business email address, you can add public domains like @gmail.com, @yahoo.com, and @hotmail.com as allowed domains for other members of your organization.
\ No newline at end of file
diff --git a/content/support/13345190-get-started-with-claude-cowork.md b/content/support/13345190-get-started-with-claude-cowork.md
index bbb9be7b62..b88926a8a5 100644
--- a/content/support/13345190-get-started-with-claude-cowork.md
+++ b/content/support/13345190-get-started-with-claude-cowork.md
@@ -178,7 +178,7 @@ To set global instructions:
3. Type your instructions in the text box and click "Save":
-
+
### Folder instructions
diff --git a/content/support/13371040-log-in-to-your-console-account.md b/content/support/13371040-log-in-to-your-console-account.md
index baeb9f69d3..15054a32f6 100644
--- a/content/support/13371040-log-in-to-your-console-account.md
+++ b/content/support/13371040-log-in-to-your-console-account.md
@@ -2,7 +2,7 @@
When you navigate to the **[Claude Console](https://platform.claude.com)**, you will see two different options for logging in to your Console account.
-
+
## Continue with Google
diff --git a/content/support/13641943-visual-and-interactive-content.md b/content/support/13641943-visual-and-interactive-content.md
index 831e5dc147..f774e0a6d3 100644
--- a/content/support/13641943-visual-and-interactive-content.md
+++ b/content/support/13641943-visual-and-interactive-content.md
@@ -18,7 +18,7 @@ Claude can show current weather conditions and forecasts when you ask about the
Claude automatically displays temperatures in Fahrenheit for US locations and Celsius for everywhere else.
-
+
Weather is powered by Google Maps ().
@@ -28,7 +28,7 @@ When you ask about recipes, Claude can display formatted recipe cards that are e
**Note:** Visual recipe cards are available on web and desktop only. On mobile, Claude provides recipe information as text in the conversation.
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### Custom visuals
@@ -76,7 +76,7 @@ For example, if you ask Claude to help you plan a trip, it might ask you to:
This content appears at the bottom of the chat. You can still type a response if you prefer.
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+
---
diff --git a/content/support/13837440-use-plugins-in-claude.md b/content/support/13837440-use-plugins-in-claude.md
index 84fe74aecc..99fed441c0 100644
--- a/content/support/13837440-use-plugins-in-claude.md
+++ b/content/support/13837440-use-plugins-in-claude.md
@@ -58,7 +58,7 @@ In Cowork, open the "Cowork" tab first, then open **Customize**.
You can also upload a custom plugin file if you built one yourself. On Team and Enterprise plans, a colleague can share a plugin with you directly instead of sending you the file. See **[Use a plugin shared with you](#h_ef985546b4)** below. Plugins you add in Claude on the web or in Claude Desktop are saved to your account, not to your computer, so they follow you to chat, Cowork, and Claude Code.
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+
If you're on the Enterprise plan and your organization has skill scanning turned on, plugins are checked for malicious content when they're installed or updated. A plugin with malicious content is blocked, and one that may carry risk shows a caution banner. Learn more about **[skill and plugin scanning](https://support.claude.com/en/articles/15927065)**.
@@ -68,7 +68,7 @@ If you're on the Enterprise plan and your organization has skill scanning turned
Each plugin you add brings skills and commands you can use while working with Claude. Type "/" or click the "+" button to see the available skills from your plugins, in chat and in Cowork. In Cowork, you can also run a plugin's command by typing `/plugin-name:command`. Click any skill to see its details.
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+
---
diff --git a/content/support/13947068-assign-tasks-from-anywhere-in-claude-cowork.md b/content/support/13947068-assign-tasks-from-anywhere-in-claude-cowork.md
index 2bacc1f905..c7a5b0db5e 100644
--- a/content/support/13947068-assign-tasks-from-anywhere-in-claude-cowork.md
+++ b/content/support/13947068-assign-tasks-from-anywhere-in-claude-cowork.md
@@ -52,11 +52,11 @@ Follow these steps to get started:
5. You’ll land on a page describing the functionality. Click “Get started”:
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+
6. On the next screen, you can give Claude access to your files and keep your computer awake by toggling those on:
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+
7. Click “Finish setup.”
diff --git a/content/support/14116274-organize-your-tasks-with-projects-in-claude-cowork.md b/content/support/14116274-organize-your-tasks-with-projects-in-claude-cowork.md
index 21512eef0e..245974cd46 100644
--- a/content/support/14116274-organize-your-tasks-with-projects-in-claude-cowork.md
+++ b/content/support/14116274-organize-your-tasks-with-projects-in-claude-cowork.md
@@ -16,23 +16,23 @@ The new Claude experience, which combines chat and Cowork, is rolling out to Pro
Find **Projects** in the left navigation panel and click the “+” button to see the three different ways to create a project:
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+
### Start from scratch
Selecting “Start from scratch” allows you to set up a new folder with instructions and files:
-
+
### Import from a Claude project
After selecting “Import from project,” you’ll see a “Search projects in Chat…” field:
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+
Clicking into the field will display a drop-down showing your recent projects, but you can also use it to search all your projects. After you select a chat project (bulk upload is not supported), you can name the new Cowork project and choose where to save it on your computer:
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+
Clicking “Create” will transfer the files and instructions from your existing Claude project and create a new Cowork project.
@@ -40,11 +40,11 @@ Clicking “Create” will transfer the files and instructions from your existin
If you select “Use an existing folder,” you’ll be prompted to pick a file to use as context for the new Cowork project:
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+
After selecting a folder, you can name the new Cowork project, choose where to save it on your computer, add instructions, and attach any additional files. Click “Create” to start using your new project:
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+
---
diff --git a/content/support/14499648-how-scim-sync-works-for-enterprise-organizations.md b/content/support/14499648-how-scim-sync-works-for-enterprise-organizations.md
index 9457dc6b33..5e23db2a7c 100644
--- a/content/support/14499648-how-scim-sync-works-for-enterprise-organizations.md
+++ b/content/support/14499648-how-scim-sync-works-for-enterprise-organizations.md
@@ -50,7 +50,7 @@ You can trigger a manual sync from two places in your admin settings.
2. Click "Check for updates" under **SCIM sync**:
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+
3. Select whether to sync members, groups, or both.
@@ -62,7 +62,7 @@ You can trigger a manual sync from two places in your admin settings.
3. Select whether to sync members, groups, or both:
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+
**Note:** If you trigger a manual sync while background changes are processing, your organization takes the most recent change for each member or group. If multiple changes are queued for the same member or group, you may need to resync again to make sure everything applies correctly.
diff --git a/content/support/14604842-cyber-verification-program.md b/content/support/14604842-cyber-verification-program.md
index 749395f516..9043264afa 100644
--- a/content/support/14604842-cyber-verification-program.md
+++ b/content/support/14604842-cyber-verification-program.md
@@ -12,7 +12,7 @@ Our generally available models can still be used by all users for secure code re
## Access tiers
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+
## How to apply
diff --git a/content/support/15330088-set-a-default-model-for-your-organization.md b/content/support/15330088-set-a-default-model-for-your-organization.md
index 7919d07b7b..770b70b7b3 100644
--- a/content/support/15330088-set-a-default-model-for-your-organization.md
+++ b/content/support/15330088-set-a-default-model-for-your-organization.md
@@ -50,7 +50,7 @@ The organization default applies to every member. To set it:
4. Click “Save changes.”
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+
---
diff --git a/content/support/15694740-manage-model-access-for-your-organization.md b/content/support/15694740-manage-model-access-for-your-organization.md
index 032bae1e40..468960387f 100644
--- a/content/support/15694740-manage-model-access-for-your-organization.md
+++ b/content/support/15694740-manage-model-access-for-your-organization.md
@@ -42,9 +42,9 @@ The organization setting is the ceiling. A role can't grant access to a model th
If any custom role uses the model you’re disabling as its default, you’ll be prompted to change that role’s default before the change can be saved.
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+
-
+
---
@@ -78,7 +78,7 @@ If any custom role has an effort cap higher than the new organization cap for th
Only models the role grants access to can be selected as that role’s default model.
-
+
---
@@ -96,7 +96,7 @@ Effort limits determine how much computation members on a role can apply per res
5. Click "Save" to save your changes.
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+
Members on the role see only effort levels at or below the cap in their model menu. Note that available effort levels differ depending on the model, and some models don’t support effort level settings at all. For an explanation of each level, see **[Change the model, effort, and thinking settings](https://support.claude.com/en/articles/8664678)**.
diff --git a/content/support/15936181-get-started-with-1password-for-claude.md b/content/support/15936181-get-started-with-1password-for-claude.md
index b13a6ae6fc..6316e9806a 100644
--- a/content/support/15936181-get-started-with-1password-for-claude.md
+++ b/content/support/15936181-get-started-with-1password-for-claude.md
@@ -52,7 +52,7 @@ Once the requirements are in place, you can set up 1Password from a few places i
4. Toggle on **Password managers**:
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+
Once enabled, eligible users will see the discovery options above. Users still need to install and set up the required apps and extensions themselves.
diff --git a/content/support/16607638-understanding-your-pro-or-max-plan-invoices.md b/content/support/16607638-understanding-your-pro-or-max-plan-invoices.md
index 795851ec61..bf65df6b67 100644
--- a/content/support/16607638-understanding-your-pro-or-max-plan-invoices.md
+++ b/content/support/16607638-understanding-your-pro-or-max-plan-invoices.md
@@ -40,7 +40,7 @@ You can also open any invoice from your account:
**Amount due.** The invoice total minus any applied balance. This is what your payment method was charged.
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## Billing details on your invoice
diff --git a/content/support/16951679-use-claude-in-google-docs-sheets-and-slides.md b/content/support/16951679-use-claude-in-google-docs-sheets-and-slides.md
index 06ef7fe274..a3b42feb46 100644
--- a/content/support/16951679-use-claude-in-google-docs-sheets-and-slides.md
+++ b/content/support/16951679-use-claude-in-google-docs-sheets-and-slides.md
@@ -28,11 +28,11 @@ If your organization already allows Marketplace apps, this takes about two minut
2. Open a Google Docs, Sheets, or Slides file and go to Extensions > Claude > “Open Claude":
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+
3. The first time, Google asks you to allow two permissions. Review them and click "Allow":
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+ 
4. Sign in with your Claude account in the sidebar, and optionally enable your connectors.
diff --git a/content/support/17203415-set-up-claude-for-intune.md b/content/support/17203415-set-up-claude-for-intune.md
index a7b7083ff5..b0a215e436 100644
--- a/content/support/17203415-set-up-claude-for-intune.md
+++ b/content/support/17203415-set-up-claude-for-intune.md
@@ -70,25 +70,25 @@ To add Claude for Intune for enrolled company-owned devices:
1. In the Microsoft Intune admin center, select "Apps" from the left side navigation panel:
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+
2. Under Platforms, select "iOS/iPadOS":
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+
3. Click "+ Create." For the App type, select the "iOS store app," and click the "Select" button on the bottom:
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+
4. Search "Claude for Intune" and click the "Select" button on the bottom.
5. In **App Information**, set **Minimum operating system** to iOS 18, then click the "Next" button:
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+
6. For **Assignments**, add the groups that should get the app: under Required to install it automatically, or under Available for enrolled devices so employees can install it from Company Portal. You can use user groups or device groups.
-
+
7. Click "Next," review and create.
@@ -98,27 +98,27 @@ To add Claude for Intune for enrolled company-owned devices:
1. In the Microsoft Intune admin center, select "Apps" from the left side navigation panel:
-
+
2. Under **Manage apps**, select "Protection":
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+
3. Click "+ Create" and then select "iOS/iPadOS":
-
+
4. Enter Name in the **Basics** tab, then click "Next" to **Apps**. Set **Target policy to** "Selected apps." Click "+ Select custom apps":
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+
5. Type in the bundle ID `com.anthropic.claudeforintune`. Select it so it appears under **Selected Apps** before clicking "Select":
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+
6. In Apps, confirm the bundle ID now appears under **Custom apps** before clicking "Next":
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+
7. Configure the Data protection, Access requirements, and Conditional launch settings as needed.
diff --git a/content/support/17444462-set-up-and-manage-the-new-unified-claude-experience-for-your-enterprise-organization.md b/content/support/17444462-set-up-and-manage-the-new-unified-claude-experience-for-your-enterprise-organization.md
index 3d68b0a567..dd5f5946cf 100644
--- a/content/support/17444462-set-up-and-manage-the-new-unified-claude-experience-for-your-enterprise-organization.md
+++ b/content/support/17444462-set-up-and-manage-the-new-unified-claude-experience-for-your-enterprise-organization.md
@@ -184,11 +184,11 @@ The new unified Claude experience gets its own line in your reports. When a memb
**A page of its own.** Admins who can view analytics will find a Chat and Cowork unified page under Apps. It shows daily active users.
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+
**Across the dashboard.** You can pick "Chat and Cowork unified" in the Active users, Active members, Total spend, and Spend by model charts. The See all members table on the Overview page has a "Messages in Chat and Cowork unified" column. The Top connectors and Top skills cards don't include it yet.
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+
**Who sees it.** The page appears for every organization that can turn on the new unified Claude experience, whether or not it is on yet.
diff --git a/content/support/8114491-get-started-with-claude.md b/content/support/8114491-get-started-with-claude.md
index 68b341fd61..c9d7b9e2c8 100644
--- a/content/support/8114491-get-started-with-claude.md
+++ b/content/support/8114491-get-started-with-claude.md
@@ -36,7 +36,7 @@ You use **prompts** to communicate with Claude. The best approach is to speak to
Type your prompt into the chat interface and click the submit button to start a conversation with Claude. You can click the "+" button in the lower left or type "/" to view additional options and commands:
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+
---
diff --git a/content/support/8230524-delete-or-rename-a-conversation.md b/content/support/8230524-delete-or-rename-a-conversation.md
index 1c1f3e14fd..1433518f52 100644
--- a/content/support/8230524-delete-or-rename-a-conversation.md
+++ b/content/support/8230524-delete-or-rename-a-conversation.md
@@ -44,15 +44,15 @@ These steps apply to Claude for iOS, listed on the App Store as Claude by Anthro
4. If deleting, tap "Delete" again in the confirmation prompt.
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+
-
+
You can also delete the conversation you have open: tap the "⋯" button in the top right corner, tap "Delete," then confirm.
-
+
-
+
## Delete or rename a conversation on Claude for Android
@@ -66,9 +66,9 @@ These steps apply to the Claude for Android, listed on Google Play as Claude by
3. If deleting, tap "Delete" again in the confirmation prompt.
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+
-
+
**To delete multiple conversations at once:**
@@ -78,9 +78,9 @@ These steps apply to the Claude for Android, listed on Google Play as Claude by
3. Tap the trash icon, then tap "Delete" in the confirmation prompt.
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+
-
+
## What happens when you delete a conversation
diff --git a/content/support/8325618-paid-plan-billing-faqs.md b/content/support/8325618-paid-plan-billing-faqs.md
index 1dee79689f..5ef7e451ad 100644
--- a/content/support/8325618-paid-plan-billing-faqs.md
+++ b/content/support/8325618-paid-plan-billing-faqs.md
@@ -50,7 +50,7 @@ There's no separate option to remove a card, and updating to a new card replaces
If you want to use a name other than the one tied to your payment method, check the "Use a different name on invoices" box when adding or updating your payment method in **[Settings > Billing](https://claude.ai/settings/billing)**.
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+
## How can I edit a paid invoice?
diff --git a/content/support/8887527-customizing-your-appearance-settings.md b/content/support/8887527-customizing-your-appearance-settings.md
index 9d383cae1c..5a4e444ab1 100644
--- a/content/support/8887527-customizing-your-appearance-settings.md
+++ b/content/support/8887527-customizing-your-appearance-settings.md
@@ -8,7 +8,7 @@
3. Select from Light, Match System, and Dark under **Color mode**.
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+
## How to change your font
@@ -16,10 +16,10 @@
2. Select from Default, Match System, and Dyslexic Friendly.
-
+
## Can I disable the sidebar?
It's not currently possible to completely disable the sidebar. You can click the button on the top right of the sidebar to open or close it.
-
\ No newline at end of file
+
\ No newline at end of file
diff --git a/content/support/9267400-move-your-personal-claude-account-to-a-team-or-enterprise-organization.md b/content/support/9267400-move-your-personal-claude-account-to-a-team-or-enterprise-organization.md
index 28c2da6ff4..adcd4c2215 100644
--- a/content/support/9267400-move-your-personal-claude-account-to-a-team-or-enterprise-organization.md
+++ b/content/support/9267400-move-your-personal-claude-account-to-a-team-or-enterprise-organization.md
@@ -132,7 +132,7 @@ For the full walkthrough of your options, deadlines, and what happens to your su
You may have both a personal account and an organization account tied to the same email address. You can switch between them by clicking your initials or name in the lower left corner of the screen.
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+
A blue checkmark shows which account you're currently using. Click the other account to switch to it and access its separate conversations and projects.
diff --git a/content/support/9519177-how-can-i-create-and-manage-projects.md b/content/support/9519177-how-can-i-create-and-manage-projects.md
index dcbe6db731..feb089a440 100644
--- a/content/support/9519177-how-can-i-create-and-manage-projects.md
+++ b/content/support/9519177-how-can-i-create-and-manage-projects.md
@@ -104,15 +104,15 @@ Starring a project allows for quick access from your projects and chats list, vi
You can move a standalone chat into a project by clicking on the dropdown arrow next to the chat name, then “Add to project”:
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+
Browse or search for the correct project in the **Move chat** modal that appears, then click on it to move the chat.
-
+
You can also remove chats from projects, or move them between projects, using the same dropdown menu within the chat:
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+
---