How do I install the Skill Comply skill?

Run npx skillmds@latest add yogiraja/skill-comply in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Skill Comply safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: executes scripts. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Skill Comply?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Skill Comply free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Skill Comply?

YogirajA (@yogiraja) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Skill Comply by yogiraja — Agent Skill

Name: Skill Comply
Rating: 4.2 (5 reviews)
Author: YogirajA

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. Use when checking whether agents actually follow the skills, rules, and definitions they were given, rather than assuming they do.

YogirajA Updated Sep 22, 2026

File contents

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 read-wiki, 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/testing.md

# Dry run (no cost, spec + scenarios only)
uv run python -m scripts.run --dry-run ~/.claude/skills/read-wiki/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.

---name: skill-complydescription: 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. Use when checking whether agents actually follow the skills, rules, and definitions they were given, rather than assuming they do.---# skill-comply: Automated Compliance MeasurementMeasures whether coding agents actually follow skills, rules, or agent definitions by:1. Auto-generating expected behavioral sequences (specs) from any .md file2. Auto-generating scenarios with decreasing prompt strictness (supportive → neutral → competing)3. Running `claude -p` and capturing tool call traces via stream-json4. Classifying tool calls against spec steps using LLM (not regex)5. Checking temporal ordering deterministically6. Generating self-contained reports with spec, prompts, and timelines## Supported Targets- **Skills** (`skills/*/SKILL.md`): Workflow skills like read-wiki, 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 runuv run python -m scripts.run .claude/rules/testing.md# Dry run (no cost, spec + scenarios only)uv run python -m scripts.run --dry-run ~/.claude/skills/read-wiki/SKILL.md# Custom modelsuv run python -m scripts.run --gen-model haiku --model sonnet <path>```## Key Concept: Prompt IndependenceMeasures whether a skill/rule is followed even when the prompt doesn't explicitly support it.## Report ContentsReports 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 scenario4. 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.

Frequently asked questions