Skill

skill-comply

Measures whether skills, rules, and agent definitions are actually followed by auto-generating scenarios, running agents, and reporting compliance rates.

npx claudepluginhub nassimbf/ftitos-claude-code

Tool Access

This skill uses the workspace's default tool permissions.

Preview

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

SKILL.md

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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

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/*.md): Mandatory rules like testing.md, security.md

Agent definitions (agents/*.md): Whether an agent gets invoked when expected

When to Activate

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 path/to/rules/testing.md # Dry run (no cost, spec + scenarios only) uv run python -m scripts.run --dry-run path/to/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

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
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/*.md): Mandatory rules like testing.md, security.md
Agent definitions (agents/*.md): Whether an agent gets invoked when expected

When to Activate

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 path/to/rules/testing.md

# Dry run (no cost, spec + scenarios only)
uv run python -m scripts.run --dry-run path/to/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