option

skill-comply

affaan-m/ECC affaan-m/ECC

Automatically measures whether coding agents follow skills, rules, or agent definitions by generating scenarios at multiple prompt strictness levels, running agents, classifying tool calls, and reporting compliance rates with full timelines.

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Updated time October 2, 2026

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

Usage

# 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 

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.

View on GitHub
---
name: skill-comply
description: Automatically measures whether coding agents follow skills, rules, or agent definitions by generating scenarios at multiple prompt strictness levels, running agents, classifying tool calls, and reporting compliance rates with full timelines.
---

# 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.

Install skill-comply

Download and extract the skill files to your .claude/skills/ directory.

Download ZIP

Clone the repository and copy the skill files to your project.

git clone https://github.com/affaan-m/ECC/tree/main/skills/skill-comply # Copy SKILL.md to your .claude/skills/ directory

Copy Copy
Quick Setup: Copy the skill folder to .claude/skills/ Claude will automatically detect and use the skill
Repository affaan-m/ECC

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