S

skill-comply

by @affaan-mv
4.4(20)

Automatically generate AI agent behavior compliance test scenarios to verify if code agents strictly adhere to skill definitions and rule requirements.

ai-agentstest-automationprompt-engineeringquality-assurancellm-orchestrationGitHub
Installation
npx skills add https://github.com/affaan-m/everything-claude-code --skill skill-comply
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Before / After Comparison

1 组
Before

Manually writing test cases to verify AI agent behavior, manually checking each output for compliance with specifications. Takes multiple days for a single agent, with limited coverage and a high risk of missing edge cases.

After

Automatically generating a complete test suite from specification documents, including test scenarios of various strictness levels. Automatically executing and generating compliance reports, completing comprehensive verification in 2 hours.

SKILL.md

skill-comply

skill-comply: Automated Compliance Measurement

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

  • Auto-generating expected behavioral sequences (specs) from any .md file

  • Auto-generating scenarios with decreasing prompt strictness (supportive → neutral → competing)

  • Running claude -p and capturing tool call traces via stream-json

  • Classifying tool calls against spec steps using LLM (not regex)

  • Checking temporal ordering deterministically

  • 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

# 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:

  • Expected behavioral sequence (auto-generated spec)

  • Scenario prompts (what was asked at each strictness level)

  • Compliance scores per scenario

  • 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. Weekly Installs325Repositoryaffaan-m/everyt…ude-codeGitHub Stars114.8KFirst Seen6 days agoSecurity AuditsGen Agent Trust HubFailSocketWarnSnykFailInstalled oncodex314cursor281gemini-cli280github-copilot280cline280opencode280

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Statistics

Installs4.9K
Rating4.4 / 5.0
Version
Updated2026年8月7日
Comparisons1

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4.4(20)
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Compatible Platforms

🔧Claude Code

Timeline

Created2026年3月30日
Last Updated2026年8月7日
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