rule-effectiveness
Skill8 starsChanged 7 months agoMITView on GitHub
Cross-reference .claude/rules/ globs against git history to find inert rules and uncovered directories. Content quality and context cost are native — run /doctor prompt-audit and /skill-doctor for those.
In this repository20 other files it gives its agents.
- .claude/rules/agents.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- audit-projectSkill
- bootstrap-projectSkill
- capture-practiceSkill
- diff-projectSkill
- domain-extractSkill
- export-configSkill
- forge-behaviorSkill
- init-projectSkill
- learn-projectSkill
- mcp-addSkill
- plugin-generatorSkill
- reset-projectSkill
- scout-reposSkill
- session-insightsSkill
- sync-all-reposSkill
- sync-templateSkill
- update-practicesSkill
- watch-upstreamSkill
The file
We split this skill into the rules it gives an agent
9 rules. About 0 are common, 3 are distinctive, and 6 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
6
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 13
Do not re-implement either here.
- Very specific: line 17
Read all .md files in .claude/rules/.
- Very specific: line 22
If a rule has no globs: or paths: frontmatter, classify as always-loaded (loads every session regardless of files touched).
- Very specific: line 28
Run: git log --name-only --pretty=format:'' --since='3 months ago' (or configurable period).
- Very specific: line 35
If fewer than 5 sessions available, warn that results may not be representative and extend to --since='6 months ago'.
- Very specific: line 73
If directory maps to an existing stack (e.g., migrations/ → supabase), recommend adding stack rule
- Distinctive: line 74
If directory is project-specific, recommend creating a custom rule
- Very specific: line 125
Add missing rule: create .claude/rules/{{name}}.md with suggested globs
- Distinctive: line 128
Only execute with user confirmation.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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.
Scope (native-first boundary, v4.7.0): this skill owns the one measurement Claude Code has no native equivalent for — does each rule's glob match files the project actually touches. Everything else is native:
/doctor prompt-audit [path](v2.1.283+) flags rules/CLAUDE.md written for older models, references to files or commands that no longer exist, and contradictions between files — run it for content quality./skill-doctor(v2.1.252+) and/doctorreport per-skill/MCP context cost and unused skills — run them for token budget. Do not re-implement either here.
Step 1: Collect rules inventory
Read all .md files in .claude/rules/. For each:
- Extract
globs:value from YAML frontmatter - Count lines of content (excluding frontmatter)
- 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:
- Match glob against all_files_touched using bash glob expansion or fnmatch logic
- Calculate:
matched_files: count of unique files that match the globmatch_rate: % of sessions where at least 1 file matched the globtoken_cost: lines of rule content (proxy for context consumption)
For the project overall:
covered_files: files that match at least 1 rule globuncovered_files: files touched but matching no rulefile_coverage: covered / total
Step 4: Classify rules
| Classification | Criteria | Action |
| Active | match_rate > 50% | Keep — rule loads in most sessions and covers real files |
| Occasional | match_rate 10-50% | Evaluate — may be worth keeping for specific workflows (deploys, migrations) |
| Inert | match_rate < 10% | Candidate for removal — consumes tokens without matching real files |
| Always-loaded | globs: **/* or no globs | Evaluate content — is it generic enough to justify always loading? |
| Overbroad | globs: **/* but content is stack-specific | Should 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 pathFor 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: Native content + cost audit (pointer, not re-implemented)
Tell the user to run, in this order, and include the pointers in the report:
/doctor prompt-audit .claude/rules— stale-model phrasing, broken paths/commands, contradictions (content quality)./skill-doctor— context cost and usage of skills;/doctorfor MCP servers and plugins vs their cost.
For inert rules found in Step 4, the line count is a sufficient proxy — do not compute a token budget table.
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}}
── NATIVE FOLLOW-UP ──
/doctor prompt-audit .claude/rules → content quality (stale models, broken refs, contradictions)
/skill-doctor → context cost of skills; /doctor for MCP + plugins
── 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}}.mdwith suggested globs - Split overbroad rule: extract stack-specific content to narrower-glob rule
Only execute with user confirmation. Show diff before applying.
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Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

