diff --git a/README.ja.md b/README.ja.md index ecce707..32a8808 100644 --- a/README.ja.md +++ b/README.ja.md @@ -93,7 +93,7 @@ robocoが常時運用している**GPUスポット確保可能性(プレイス cdkのコンテキストとscripts/*.shを直接扱う代わりに、統合CLIを使うことができる: ```bash -npm install -g @serithemage/tkf # tkfコマンドをインストール +npm install -g @roboco/token-forge # tkfコマンドをインストール # もしくはソースからインストール: # npm install && npm run build && npm link tkf model list # 検証済みモデルカタログ diff --git a/README.ko.md b/README.ko.md index 48b0c79..f09c515 100644 --- a/README.ko.md +++ b/README.ko.md @@ -87,7 +87,7 @@ roboco가 상시 운영하는 **GPU 스팟 확보 가능성(배치점수) × 가 cdk 컨텍스트와 scripts/*.sh를 직접 다루는 대신 통합 CLI를 쓸 수 있다: ```bash -npm install -g @serithemage/tkf # tkf 명령 설치 +npm install -g @roboco/token-forge # tkf 명령 설치 # 또는 소스에서 설치: # npm install && npm run build && npm link tkf model list # 검증된 모델 카탈로그 diff --git a/README.md b/README.md index 0a197ee..e40628d 100644 --- a/README.md +++ b/README.md @@ -103,7 +103,7 @@ Instead of working with cdk context flags and scripts/*.sh directly, you can use unified CLI: ```bash -npm install -g @serithemage/tkf # install the tkf command +npm install -g @roboco/token-forge # install the tkf command # or, to install from source: # npm install && npm run build && npm link tkf model list # verified model catalog diff --git a/package-lock.json b/package-lock.json index ac01637..6b727ac 100644 --- a/package-lock.json +++ b/package-lock.json @@ -1,12 +1,12 @@ { - "name": "@serithemage/tkf", - "version": "1.0.0", + "name": "@roboco/token-forge", + "version": "1.0.1", "lockfileVersion": 3, "requires": true, "packages": { "": { - "name": "@serithemage/tkf", - "version": "1.0.0", + "name": "@roboco/token-forge", + "version": "1.0.1", "license": "MIT", "dependencies": { "@aws-sdk/client-auto-scaling": "^3.1116.0", diff --git a/package.json b/package.json index 0ea7d66..f79f2af 100644 --- a/package.json +++ b/package.json @@ -1,6 +1,6 @@ { - "name": "@serithemage/tkf", - "version": "1.0.0", + "name": "@roboco/token-forge", + "version": "1.0.1", "description": "Private vibe-coding LLM in your own AWS account — open-weight models on 100% spot instances with placement-score intelligence", "keywords": [ "llm",