Individual skill
skill-comply
可视化技能、规则和代理定义是否被实际遵循——自动生成3种提示严格级别的场景,运行代理,分类行为序列,并报告完整工具调用时间线的合规率
docs/zh-CN/skills/skill-comply/SKILL.md
Source commit d2ef2680594f9a17526a6e1a2e18b3d242c5d17b
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- Yes
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Network or broad shell
- Last checked
- Nov 9, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
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Repository context
- Repository stars (not skill ratings)
- 300,266
- Repository last updated
- Nov 6, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai-agents Repository topic
- anthropic Repository topic
- claude Repository topic
- claude-code Repository topic
- developer-tools Repository topic
- llm Repository topic
- mcp Repository topic
- productivity Repository topic
- engineering Derived category
Files and excerpt
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# skill-comply:自动化合规性测量
通过以下方式测量编码代理是否实际遵循技能、规则或代理定义:
1. 从任意 .md 文件自动生成预期行为序列(规范)
2. 自动生成提示严格程度递减的场景(支持性 → 中性 → 竞争性)
3. 运行 `claude -p` 并通过 stream-json 捕获工具调用轨迹
4. 使用 LLM(而非正则表达式)将工具调用分类到规范步骤
5. 确定性检查时间顺序
6. 生成包含规范、提示和时间线的自包含报告
## 支持的目标
* **技能**(`skills/*/SKILL.md`):工作流技能,如搜索优先、TDD 指南