wolfe-jam/faf-skills/repo-maintainer
Claude Code and agent skill by wolfe-jam/faf-skills
- community
Checking that the SKILL.md file is still in the repository.
Audits leftover test artifacts, dependencies, CI workflows, docs that have drifted from the code, git hygiene and FAF alignment, then writes a cleanup plan ordered by impact. Use when someone wants a repository cleaned up or checked: "clean up this repo", "audit the repo", "health check before the release". Changes nothing without approval.
Install
npx vskill@latest install wolfe-jam/faf-skills/repo-maintainerSKILL.md
<!-- faf:end -->
Repo Maintainer - Championship Repository Hygiene
"When brakes must work flawlessly, so must our repos."
When to Use This Skill
Activate when:
- User types
/repo-maintainer - User says "clean up this repo" or "audit the repo"
- Starting maintenance on a repository
- After major refactoring or before releases
- Monthly/quarterly repo health checks
- Onboarding to a new codebase
What This Skill Does
Phase 1: Comprehensive Audit
Systematically checks 7 critical areas:
1. Artifact Detection
Detection Strategy:
- Check
git statusfor untracked patterns - Scan for common artifact extensions
- Compare against .gitignore
- Find large files (>1MB) in working directory
2. Dependency Health
Red Flags:
- Packages with security vulnerabilities
- EOL runtime versions (Node 16, Python 3.7)
- Duplicate dependencies (lodash + lodash.merge)
- Unused dependencies (installed but never imported)
3. CI/CD Alignment
Common Fixes:
- Remove EOL runtimes (e.g. Node 16) from release workflows
- Align Node versions across all workflows (current LTS lines, e.g. 22/24)
- Pin packages that break under ESM resolution
4. Documentation Sync
FAF-Specific:
- project.faf reflects current state
- CLAUDE.md written from project.faf (
faf sync, one way) - .faf-dna not churning unnecessarily
5. Git Hygiene
Pattern Recognition:
6. Code Quality Signals
7. FAF Ecosystem Health
For FAF projects specifically:
For MCP servers:
Phase 2: Cleanup Plan Generation
After audit, generate prioritized task list:
Phase 3: Auto-Fix (Optional)
For safe, non-breaking fixes:
Workflow
Step 1: Initial Assessment
Step 2: Systematic Audit
Run checks in order of priority:
- Critical first - CI/CD failures, security issues
- Medium next - Dependencies, documentation gaps
- Low priority - Code quality signals, nice-to-haves
Step 3: Generate Report
Create structured report with:
- Overall health score (0-100%)
- Critical/Medium/Low sections
- Effort estimates
- Auto-fix availability
- Recommended action plan
Step 4: Execute (with approval)
Ask user:
- "Run auto-fix for safe items?"
- "Create cleanup branch?"
- "Open issues for manual items?"
Never make changes without explicit approval.
MCP Server Maintenance
Additional MCP Checks:
MCP Cleanup Checklist:
- [ ] Remove test artifacts
- [ ] Update dependencies
- [ ] Align workflows (supported Node LTS lines only)
- [ ] Verify MCP tools still work
- [ ] Update README examples
- [ ] Check CHANGELOG current
- [ ] Verify published to npm
- [ ] Confirm registry listing accurate
✪ Tier System (Aligned with FAF)
CRITICAL: Use Official FAF Tiers for All Scoring
| Score | Tier | Symbol | Status | |
|---|---|---|---|---|
| 100% | Trophy | ✪ | AI is optimized to code | |
| 99% | Gold | ★ | Exceptional | |
| 95% | Silver | ◆ | Top tier | |
| 85% | Bronze | ◇ | Production ready | |
| 70% | Green | ● | Solid foundation | |
| 55% | Yellow | ● | Needs improvement | |
| 1% | Red | ○ | Major work needed | |
| 0% | White | ♡ | Empty |
The score is deterministic — same input → same score, every time. FAF doesn't lie.
Note: Big Orange is an HONOR, not a score or a badge. It recognizes sustained excellence across multiple criteria; it is never calculated from a single score.
Apply These Tiers to:
- Overall repo health score
- Individual category scores (CI/CD, Dependencies, etc.)
- Summary reports
- Cleanup recommendations
Examples:
Related Skills
/wjttc-builder·/wjttc-tester- generate + run championship-grade tests before a release/faf-expert- master the.fafformat + score the repo's AI-readiness
Best Practices
1. Run Regularly
- After major refactors
- Before releases
- Monthly maintenance
- When onboarding new devs
2. Prioritize Impact
- Fix breaking issues first (CI/CD, security)
- Document before cleaning (understand why artifacts exist)
- Test after cleanup (ensure nothing broke)
3. Track Progress
- Use TodoWrite for multi-step cleanups
- Create issues for manual items
- Document decisions in CLAUDE.md
4. Automate Where Safe
- .gitignore additions ✓
- CHANGELOG drafts ✓
- Workflow alignment ✓
- Breaking changes ✗ (need review)
Example Session
The Championship Promise
"Pit crews service the car between every race.Your repos deserve the same attention."
Repo Maintainer - Championship Repository Hygiene "When brakes must work flawlessly, so must our repos."
Security
- Security scanPassed, 95 of 100Pattern checks on the skill's files.
- Model reviewPassed
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/repo-maintainer/SKILL.md
Popularity
- Repository stars
- 4
- 7-day trend score
- 8
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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