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Rule effectiveness

Skill luiseiman/dotforge/skills/rule-effectiveness

Configuration governance for Claude Code. Bootstrap, audit, sync, and evolve .claude/ across projects.

Install
npx -y skills add luiseiman/dotforge --skill rule-effectiveness

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

SKILL.md

5.2 KB, as published. Nobody here has run it

Rule Effectiveness Analysis

Analyze the effectiveness of .claude/rules/ in the current project by cross-referencing rule globs against actual file activity from git history.

Step 1: Collect rules inventory

Read all .md files in .claude/rules/. For each:

  1. Extract globs: value from YAML frontmatter
  2. Count lines of content (excluding frontmatter)
  3. Record filename and glob pattern

If a rule has no globs: or paths: frontmatter, classify as always-loaded (loads every session regardless of files touched).

Rules with globs: load eagerly at session start. Rules with paths: + alwaysApply: false load lazily (only when a matching file is touched). Note: paths: must be unquoted CSV — YAML arrays and quoted strings fail silently.

Step 2: Collect file activity from git history

Run: git log --name-only --pretty=format:'' --since='3 months ago' (or configurable period).

Parse output to build:

  • session_files: group files by commit date (approximate 1 day = 1 session)
  • total_sessions: count distinct dates with commits
  • all_files_touched: unique set of all files modified

If fewer than 5 sessions available, warn that results may not be representative and extend to --since='6 months ago'.

Step 3: Cross-reference rules vs activity

For each rule with a glob pattern:

  1. Match glob against all_files_touched using bash glob expansion or fnmatch logic
  2. Calculate:
    • matched_files: count of unique files that match the glob
    • match_rate: % of sessions where at least 1 file matched the glob
    • token_cost: lines of rule content (proxy for context consumption)

For the project overall:

  • covered_files: files that match at least 1 rule glob
  • uncovered_files: files touched but matching no rule
  • file_coverage: covered / total

Step 4: Classify rules

ClassificationCriteriaAction
Activematch_rate > 50%Keep — rule loads in most sessions and covers real files
Occasionalmatch_rate 10-50%Evaluate — may be worth keeping for specific workflows (deploys, migrations)
Inertmatch_rate < 10%Candidate for removal — consumes tokens without matching real files
Always-loadedglobs: **/* or no globsEvaluate content — is it generic enough to justify always loading?
Overbroadglobs: **/* but content is stack-specificShould have narrower globs to avoid loading in wrong contexts

Step 5: Detect coverage gaps

From uncovered_files, group by directory prefix. Report directories with >5 uncovered files:

SIN COBERTURA:
  src/utils/     — 12 files touched, no rule covers this path
  scripts/       — 8 files touched, no rule covers this path
  migrations/    — 5 files touched, no rule covers this path

For each gap, suggest:

  • If directory maps to an existing stack (e.g., migrations/ → supabase), recommend adding stack rule
  • If directory is project-specific, recommend creating a custom rule

Step 6: Token optimization analysis

Calculate approximate token impact:

  • Always-loaded rules: sum of all lines (loaded every session)
  • Active rules: weighted by match_rate × lines
  • Inert rules: full line count = wasted tokens
TOKEN BUDGET:
  Always loaded:  _common.md (35 lines) + agents.md (52 lines) + memory.md (18 lines) = 105 lines/session
  Active rules:   backend.md (33 lines × 95%) + testing.md (30 lines × 78%) = ~55 lines avg/session
  Inert rules:    ios.md (34 lines × 0%) = 34 lines WASTED per session when loaded

  POTENTIAL SAVINGS: Remove ios.md → save ~34 lines of context per session

Step 7: Generate report

═══ RULE EFFECTIVENESS — {{project}} ═══
Period: last {{N}} months ({{total_sessions}} sessions)
Rules: {{rule_count}} files, {{total_lines}} lines

── ACTIVE (keep) ──
  {{rule.md}}     — {{match_rate}}% match, {{matched_files}} files, {{lines}} lines
  ...

── OCCASIONAL (evaluate) ──
  {{rule.md}}     — {{match_rate}}% match, {{matched_files}} files
  ...

── INERT (candidates for removal) ──
  {{rule.md}}     — {{match_rate}}% match, {{matched_files}} files ← {{reason}}
  ...

── ALWAYS-LOADED ({{total_lines}} lines/session) ──
  {{rule.md}}     — {{lines}} lines, globs: **/*
  ...

── COVERAGE ──
  Files covered by rules:   {{covered}}/{{total}} ({{coverage}}%)
  Gaps: {{gap_dirs}}

── TOKEN OPTIMIZATION ──
  Current avg load:    ~{{current}} lines/session
  After pruning inert: ~{{pruned}} lines/session
  Potential savings:   ~{{savings}} lines/session ({{pct}}% reduction)

── RECOMMENDATIONS ──
1. {{action}} — {{reason}}
2. ...

Step 8: Offer automated fixes

For each recommendation, offer to execute:

  • Remove inert rule: rm .claude/rules/{{file}} (with confirmation)
  • Narrow glob: edit frontmatter to restrict to actual file patterns
  • Add missing rule: create .claude/rules/{{name}}.md with suggested globs
  • Split overbroad rule: extract stack-specific content to narrower-glob rule

Only execute with user confirmation. Show diff before applying.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.