Clarify project positioning and evidence scope in both READMEs

README.md

@@ -193,39 +193,47 @@ The [checkpoint format and scoring rules](docs/methodology.md#checkpoint-analysi
 include regression handling and comparability checks. Missing agent tokens and
 costs remain `null`. Caller-reported elapsed time is not a METR time horizon.
 
-## Why this project?
+## Project scope
 
-The research direction comes from executable SWE environments, verifier quality,
-and long-horizon evaluation. The [research report](docs/research.zh-CN.md)
-connects the design to SWE-bench, SWE-Gym, SWE-smith, R2E-Gym, SWE-rebench,
-METR, RE-Bench, SWE-EVO, and current Terminal-Bench/Harbor work.
-The [paper catalog](research/papers.json) records primary sources and verified
-publication status.
+**EvalArc audits graders and reviews evaluation evidence for coding and
+tool-using agents.** Executable tasks, outcome checks outside the candidate,
+revision comparisons and portable reports help developers assess whether
+results meet acceptance requirements and grading rules detect declared defects.
 
-EvalArc's intended place is an **audit layer alongside existing environment
-and training frameworks**. Harbor already supports multi-step tasks and separate
-verifier environments; neither is claimed as an invention here.
-Native Harbor task export, oracle/NOP execution and ATIF 1.8 records are available as [bounded research integrations](docs/research-pilots.md). A general production adapter and Prime Intellect integration remain future work.
+The project serves as an audit layer within existing evaluation environments
+and experiment workflows. It focuses on three questions: does the result meet
+the task contract, did a change introduce a regression, and can the conclusion
+be checked against the original records? See the
+[architecture](docs/architecture.md) and [methodology](docs/methodology.md)
+for task contracts, scoring rules and integration scope.
 
-## Project name
+Native Harbor task export, oracle/NOP execution and ATIF 1.8 records are
+available as [bounded research integrations](docs/research-pilots.md).
+A general production adapter, Prime Intellect integration and calibrated
+long-horizon task sets remain future work.
 
-The initial local prototype was called GradeRail. EvalArc is the selected
-project name; the package, Python imports, command, and new report schemas use
-`evalarc`. See [migration notes](docs/migration.md) for the identifier changes.
-The [naming review](docs/naming.zh-CN.md) preserves the original search snapshot.
+## Research basis
+
+Software-engineering agent evaluation, executable training environments and
+verifier reliability inform the design. The [research report](docs/research.zh-CN.md)
+explains the technical motivation and engineering references; the
+[paper catalog](research/papers.json) records paper sources, versions and
+publication status as of the documented search.
 
 ## Scope and evidence
 
-The tasks, references, fault controls, and seeds are all public development material.
-Different seeds do not establish uncontaminated evaluation. Detected
-defects do not prove resistance to arbitrary reward hacking. There are no
-frontier-model results, human time baselines, RL gains, or claimed SOTA results.
-See the [coding audit](examples/audit/index.html),
-[support audit](examples/support-audit/index.html), and
-[validation record](docs/validation.md) for the checks actually run.
+The public records validate graders and the review workflow. Tasks, reference
+implementations, fault controls and random seeds are public. Detection results
+apply to the declared defects, selected cases and recorded execution conditions.
+Changing seeds alone does not create an independent held-out evaluation or
+establish that the data was excluded from training.
 
-Task difficulty, diversity, independent faults, and transfer to real model
-failures must be established before this becomes a research benchmark.
+The [coding audit](examples/audit/index.html),
+[support audit](examples/support-audit/index.html) and
+[validation record](docs/validation.md) provide inspectable implementation evidence.
+Coverage of unknown defects, resistance to reward hacking, model capability
+rankings and training transfer require separate evaluation with independent
+data and an appropriate experimental design.
 
 ## Development
 
@@ -243,7 +251,8 @@ ruff format --check .
 python -m build
 ```
 
-See [CONTRIBUTING.md](CONTRIBUTING.md), [SECURITY.md](SECURITY.md), and
-[LICENSE](LICENSE). The [task-author guide](docs/task-authoring.md) explains
+See [CONTRIBUTING.md](CONTRIBUTING.md), [SECURITY.md](SECURITY.md),
+[migration notes](docs/migration.md), and [LICENSE](LICENSE).
+The [task-author guide](docs/task-authoring.md) explains
 the current built-in extension points. CI includes Python checks, the Node
 policies, and Docker audits for all three task packs.

README.zh-CN.md

@@ -121,8 +121,10 @@ evalarc init workspace/durable-kv
 evalarc evaluate workspace/durable-kv --output runs/candidate
 ```
 
-Coding 场景负责评分交付物，不负责调用模型。Harbor、Prime Intellect 的原生适配，
-以及真正困难的多小时任务集，都在路线图中。
+Coding 场景评测已完成的代码交付物，模型调用与代码生成由外部工作流负责。
+Harbor 任务导出、oracle/NOP 执行和 ATIF 1.8 记录已有
+[限定范围的研究示例](docs/research-pilots.md)；通用生产适配、Prime Intellect
+集成与经过难度标定的长程任务集仍在规划中。
 
 ## 工具型智能体与 JavaScript
 
@@ -146,24 +148,33 @@ Python 继续用于任务、评分和研究集成；候选程序通过 JSONL 与
 TypeScript 可编译为 JavaScript 使用这一接口，但当前没有 TypeScript SDK，
 也没有已验证的 Rust 实现。详见[命令配置](docs/candidate-commands.md)。
 
-## 项目名称
+## 项目定位
 
-项目已由本地原型名 GradeRail 更名为 **EvalArc**。仓库、Python 包、
-导入路径、CLI、新报告 schema 与环境变量均使用新名称。
-具体变化见[迁移说明](docs/migration.md)，原始名称检索记录保留在
-[命名复评](docs/naming.zh-CN.md)中。
+**EvalArc 为代码型与工具型智能体提供评分器审计和评测证据复核。**
+通过可执行任务、候选程序之外的结果检查、版本对照与可离线交付的报告，
+帮助开发者判断任务结果是否满足验收要求，以及评分规则能否检出已声明的行为缺陷。
 
-## 调研结论
+项目作为现有评测环境与实验流程中的审计层，关注三个问题：
+结果是否满足任务约定、变更是否引入回归、结论能否依据原始记录复核。
+任务契约、评分方法与集成范围见[架构说明](docs/architecture.md)和
+[方法说明](docs/methodology.md)。
 
-我更看好“高质量工程环境的评分器审计”这个切口：有清晰的工程产物，
-可与已有平台协作，也能进一步研究评分漏洞和训练迁移效果。
-这是一项基于文献与现有项目的方向判断，不是对热度、增长或商业结果的保证。
+## 研究依据
 
-调研区分已确认顶会论文、近期预印本和官方工程公告。Mechanize 融资公告已核实；
-另查到 Business Insider 2026 年 9 月 11 日报道人才交易已完成，最终条款未披露。
-“融资后 103 天”对应到最初报道日期，不代表谈判当天才启动。
-原始来源和区别见[调研报告](docs/research.zh-CN.md)。
+项目设计参考软件工程智能体评测、可执行训练环境与验证器可靠性研究。
+技术依据与工程参考见[研究报告](docs/research.zh-CN.md)；
+[文献目录](research/papers.json)记录论文来源、版本及检索时的发表状态。
 
-公开 seed 不是隐藏测试；对照全被识别也不代表能防住所有 reward hacking。
-[Coding 报告](examples/audit/index.html)和[工单报告](examples/support-audit/index.html)
-展示的是评分器审计结果，不能作为模型能力榜单。
+## 评测范围与边界
+
+当前公开记录用于验证评分器和复核流程，任务、参考实现、缺陷对照与随机种子均公开。
+缺陷检出结果仅适用于已声明缺陷、既定用例和记录的运行条件；更换随机种子本身
+不构成独立留出测试，也不能据此确认数据未被用于训练。
+
+[代码审计报告](examples/audit/index.html)、[工单审计报告](examples/support-audit/index.html)
+和[验证记录](docs/validation.md)提供可检查的实现证据。
+未知缺陷覆盖、抗评分投机（reward hacking）能力、模型能力排名及训练迁移收益，
+需要通过独立数据与相应实验设计另行评估。
+
+开发与维护：[贡献指南](CONTRIBUTING.md) · [安全边界](SECURITY.md) ·
+[版本迁移](docs/migration.md) · [许可证](LICENSE)。

docs/migration.md

@@ -104,9 +104,10 @@ are regenerated by execution, not by relabeling old JSON.
 
 ## Original local rename: GradeRail → EvalArc
 
-The project was renamed before its first public package release. EvalArc keeps
-the existing Durable KV task contract and grading weights. Runtime identifiers
-change as follows:
+The [historical naming review](naming.zh-CN.md) preserves the original decision
+and search snapshot. The project was renamed before its first public package
+release. EvalArc keeps the existing Durable KV task contract and grading weights.
+Runtime identifiers change as follows:
 
 | Item | Initial local prototype | Selected name |
 | --- | --- | --- |