PR Auto-Improvement Skill

SkillDev tools

Opt-in post-PR analysis and improvement suggestions for code quality enhancement

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the PR Auto-Improvement Skill skill

What this skill tells your AI

The instructions your AI receives, as published by baekenough/oh-my-customcode in .claude/skills/pr-auto-improve/SKILL.md and read by ahel’s review.

Analyzes pull requests after creation and suggests targeted improvements. Strictly opt-in — never runs automatically. User must explicitly request PR improvement.

Advisory-only — suggests improvements, never force-pushes or modifies PRs without approval (R010).

Activation

TriggerBehavior
User says "improve this PR"Activate analysis
User says "review PR #N"Activate analysis
PR created automaticallyDo NOT activate (opt-in only)
CI fails on PRSuggest activation, do not auto-run

Analysis Pipeline

1. Fetch PR diff (gh pr diff)
2. Categorize changes by type:
   - New code → check patterns, naming, structure
   - Modified code → check consistency, regression risk
   - Deleted code → check for orphaned references
3. Run improvement checks (see checklist below)
4. Generate improvement report
5. User approves → create follow-up commit(s)

Improvement Checklist

CategoryChecks
Code QualityNaming consistency, dead code, duplication, complexity
Type SafetyMissing types, any usage, assertion safety
Error HandlingUnhandled promises, missing try-catch, error propagation
TestingMissing test coverage for new functions, edge cases
DocumentationMissing JSDoc for public APIs, outdated README refs
SecurityHardcoded values, injection risks, permission checks
PerformanceUnnecessary re-renders, N+1 queries, missing indexes

Report Format

[PR Auto-Improve] PR #{number} — {title}
├── Files analyzed: {count}
├── Improvements found: {count}
│
├── [Code Quality] ({count} items)
│   ├── {file:line} — {description}
│   └── {file:line} — {description}
│
├── [Testing] ({count} items)
│   └── {file} — Missing test for {function}
│
├── [Documentation] ({count} items)
│   └── {file:line} — {description}
│
└── Estimated effort: {low|medium|high}

Apply improvements? [Y/n/select]

Improvement Modes

ModeBehavior
allApply all suggested improvements
selectUser picks which improvements to apply
reportReport only, no changes (default)

Implementation Flow

User: "improve PR #215"
  → Orchestrator activates pr-auto-improve
  → Fetch PR diff via mgr-gitnerd
  → Analyze with appropriate expert agent(s)
  → Generate report
  → User selects improvements
  → Delegate fixes to specialist agents (R010)
  → mgr-gitnerd creates follow-up commit

Agent Selection for Fixes

File TypeAgent
*.ts, *.tsxlang-typescript-expert
*.pylang-python-expert
*.golang-golang-expert
*.ktlang-kotlin-expert
*.javalang-java-expert
*.rslang-rust-expert
Test filesqa-engineer
Docs, READMEarch-documenter
MixedMultiple agents in parallel (R009)

Integration

RuleIntegration
R009Multiple file fixes execute in parallel
R010Orchestrator coordinates analysis and fix delegation
R015Full transparency on what improvements are suggested and why
R0183+ fix agents → Agent Teams for coordination
worker-reviewer-pipelineCan chain: auto-improve → worker-reviewer for critical fixes
pipeline-guardsImprovement count capped by guard limits

Opt-In Safeguards

  • NEVER auto-activates on PR creation
  • NEVER pushes changes without user approval
  • NEVER modifies PR description or labels without approval
  • Report mode is default; changes require explicit "apply" command
  • All git operations go through mgr-gitnerd (R010)

Limitations

  • Analyzes only the PR diff, not the entire codebase
  • Cannot detect architectural issues (use dev-review for that)
  • Max 50 files per analysis (skip larger PRs with warning)
  • Does not run tests (delegates to qa-engineer if needed)

Signals

GitHub stars
34
Forks
6
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
pr-auto-improve
Source
github.com/baekenough/oh-my-customcode