# Skill Comply

> Measures whether coding agents actually follow skills, rules, or agent definitions by generating test scenarios, running agents, and classifying tool calls to report compliance rates.

- Skill: `mhassan0000/skill-comply` (Agent Skill, multi-file: 22 files)
- Install (CLI): `npx skillmds add mhassan0000/skill-comply`
- Raw SKILL.md: https://api.skillmd.com/api/skills/mhassan0000/skill-comply/raw
- Safety review: CAUTION (external: skill-scanner PASS, skillspector FAIL)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML, DevOps & Infra, Agent Building
- Tags: Agent Evaluation, Compliance, Reporting, Scenario Generation, Tool Calls
- Author: MHassan0000 (https://skillmd.com/u/mhassan0000)
- Updated: 2026-08-22
- Page: https://skillmd.com/skills/mhassan0000/skill-comply

---


# 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.