Skip to content
cccskills
FreePublished on GitHub

pr-auto-improve

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

The English summary is being prepared. Showing the original description.

See how to install

Files included (1)

  • SKILL.md4.1 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

PR Auto-Improvement Skill

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DocumentationMissing JSDoc for public APIs, outdated README refs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)

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Pre-action boundary checking — validates agent tool calls against declared capabilities and task contracts

The English summary is being prepared. Showing the original description.

baekenough/second-brain15Updated Oct 8, 2026

Auto-detect project context and optimize harness — deactivate unused agents/skills, suggest missing experts, generate project profile

The English summary is being prepared. Showing the original description.

baekenough/second-brain15Updated Oct 8, 2026

Adversarial code review using attacker mindset — trust boundary, attack surface, business logic, and defense evaluation

The English summary is being prepared. Showing the original description.

baekenough/second-brain15Updated Oct 8, 2026

Apache Airflow best practices for DAG authoring, testing, and production deployment

The English summary is being prepared. Showing the original description.

baekenough/second-brain15Updated Oct 8, 2026

Alembic migration patterns for naming conventions, safety checks, expand-contract, env.py configuration, and CI integration

The English summary is being prepared. Showing the original description.

baekenough/second-brain15Updated Oct 8, 2026

Pre-routing ambiguity analysis — scores request clarity and asks clarifying questions when needed (inspired by ouroboros)

The English summary is being prepared. Showing the original description.

baekenough/second-brain15Updated Oct 8, 2026

See all skills by baekenough

Report a problem with this skill