affaan-m/ecc

skill-comply

Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines.

查看源码

使用方法

  1. 复制安装命令,在自己的智能体环境安装前先检查源码包。
  2. 从原始文档核对所需工具、凭据和支持的宿主。
  3. 说明输入材料与期望交付物,并对照来源检查输出。
npx skills add https://github.com/affaan-m/ecc --skill skill-comply

开始前需了解

  • 安装不包含模型订阅、API 额度或访问文件的权限。
  • 仓库星数和安装量反映活跃情况,不等于独立质量或安全测试。
仓库原始内容

按源仓库内容呈现,保留标题、案例、代码、表格、链接以及原文引用的演示图片。

skill-comply: Automated Compliance Measurement

Measures whether coding agents actually follow skills, rules, or agent definitions by:

  1. Auto-generating expected behavioral sequences (specs) from any .md file
  2. Auto-generating scenarios with decreasing prompt strictness (supportive → neutral → competing)
  3. Running claude -p and capturing tool call traces via stream-json
  4. Classifying tool calls against spec steps using LLM (not regex)
  5. Checking temporal ordering deterministically
  6. Generating self-contained reports with spec, prompts, and timelines

Supported Targets

  • Skills (skills/*/SKILL.md): Workflow skills like search-first, TDD guides
  • Rules (rules/common/*.md): Mandatory rules like testing.md, security.md, git-workflow.md
  • Agent definitions (agents/*.md): Whether an agent gets invoked when expected (internal workflow verification not yet supported)

When to Activate

  • User runs /skill-comply <path>
  • User asks "is this rule actually being followed?"
  • After adding new rules/skills, to verify agent compliance
  • Periodically as part of quality maintenance

Usage

bash
# Full run
uv run python -m scripts.run ~/.claude/rules/common/testing.md

# Dry run (no cost, spec + scenarios only)
uv run python -m scripts.run --dry-run ~/.claude/skills/search-first/SKILL.md

# Custom models
uv run python -m scripts.run --gen-model haiku --model sonnet <path>

Key Concept: Prompt Independence

Measures whether a skill/rule is followed even when the prompt doesn't explicitly support it.

Report Contents

Reports are self-contained and include:

  1. Expected behavioral sequence (auto-generated spec)
  2. Scenario prompts (what was asked at each strictness level)
  3. Compliance scores per scenario
  4. Tool call timelines with LLM classification labels

Advanced (optional)

For users familiar with hooks, reports also include hook promotion recommendations for steps with low compliance. This is informational — the main value is the compliance visibility itself.

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