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Skill Comply

ASecurity

Visualize whether skills

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  • Added October 16, 2026
ai-agentspythonbashtestinggitsecurity

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Scanned October 16, 2026

npx -y skills add Osama-Alzahrani-UQU/OmniAgentic --skill skill-comply --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
---
name: skill-comply
description: Visualize whether skills
metadata:
  origin: ECC
tools: Read, Bash
---
# 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.

Files in this skill

  • SKILL.md2.1 KB
  • fixtures/compliant_trace.jsonl1 KB
  • fixtures/noncompliant_trace.jsonl629 B
  • fixtures/tdd_spec.yaml1.2 KB
  • prompts/classifier.md1 KB
  • prompts/scenario_generator.md1.9 KB
  • prompts/spec_generator.md1.6 KB
  • pyproject.toml360 B
  • scripts/__pycache__/__init__.cpython-312.pyc185 B
  • scripts/__pycache__/classifier.cpython-312.pyc4.3 KB
  • scripts/__pycache__/grader.cpython-312.pyc8.1 KB
  • scripts/__pycache__/parser.cpython-312.pyc4.5 KB
  • scripts/__pycache__/report.cpython-312.pyc10.2 KB
  • scripts/__pycache__/run.cpython-312.pyc6.7 KB
  • scripts/__pycache__/runner.cpython-312.pyc10.2 KB
  • scripts/__pycache__/scenario_generator.cpython-312.pyc3 KB
  • scripts/__pycache__/spec_generator.cpython-312.pyc3.1 KB
  • scripts/__pycache__/utils.cpython-312.pyc857 B
  • scripts/classifier.py2.4 KB

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