rule-effectiveness

Analyze .claude/rules usage and generate coverage reports from git history.

8|1|Updated Mar 19, 2026
One-click install
npx skills add https://github.com/luiseiman/dotforge --skill rule-effectiveness
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: rule-effectiveness
Source: https://github.com/luiseiman/dotforge/tree/main/skills/rule-effectiveness
Command: npx skills add https://github.com/luiseiman/dotforge --skill rule-effectiveness

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyze which rules are actively used vs inert. Detect coverage gaps. Recommend pruning to reduce token consumption.

Core Features & Use Cases

  • Inventory rules by reading .claude/rules/*.md and extract globs and lines of content.
  • Cross-reference rule globs against git history to measure active coverage and identify inert or overbroad rules.
  • Generate a prioritized report with actionable recommendations to prune token usage and optimize rule sets.

Quick Start

Analyze your project's rule usage to identify active vs inert rules and generate a coverage report for the last 3 months.

Frequently Asked Questions about rule-effectiveness

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I audit Claude Code rules to find unused ones?

Rule audits identify inert .claude/rules by mining git history for session activity and matching rule globs against actual file coverage, generating a prioritized report for pruning token waste.

What is rule coverage analysis and how does it reduce token consumption?

Rule coverage analysis detects inert and overbroad .claude/rules by cross-referencing globs against git history, producing actionable recommendations to prune token waste and optimize rule sets.

How do I detect overbroad or always-loaded rules in my Claude Code project?

You detect overbroad and always-loaded rules by classifying .claude/rules globs against git history, identifying rules that trigger excessively across your project files and consume unnecessary tokens.

Can I analyze rule effectiveness using git history from the last 3 months?

Yes, rule effectiveness analysis mines git history over a specified period like 3 months to measure active rule coverage, identifying inert rules and coverage gaps for pruning.

What's the best way to prune ineffective rules without breaking active coverage?

Generate a prioritized report classifying rules into Active, Occasional, Inert, Always-loaded, and Overbroad categories, then prune only inert and overbroad rules to safely reduce token usage.

Does rule effectiveness analysis require any dependencies or external components?

No dependencies are required; rule effectiveness analysis operates standalone by parsing .claude/rules/*.md frontmatter and mining git history to produce coverage gap reports.