Pre-action boundary checking — validates agent tool calls against declared capabilities and task contracts
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Opt-in post-PR analysis and improvement suggestions for code quality enhancement
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
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).
| Trigger | Behavior |
|---|---|
| User says "improve this PR" | Activate analysis |
| User says "review PR #N" | Activate analysis |
| PR created automatically | Do NOT activate (opt-in only) |
| CI fails on PR | Suggest activation, do not auto-run |
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)
| Category | Checks |
|---|---|
| Code Quality | Naming consistency, dead code, duplication, complexity |
| Type Safety | Missing types, any usage, assertion safety |
| Error Handling | Unhandled promises, missing try-catch, error propagation |
| Testing | Missing test coverage for new functions, edge cases |
| Documentation | Missing JSDoc for public APIs, outdated README refs |
| Security | Hardcoded values, injection risks, permission checks |
| Performance | Unnecessary re-renders, N+1 queries, missing indexes |
[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]
| Mode | Behavior |
|---|---|
all | Apply all suggested improvements |
select | User picks which improvements to apply |
report | Report only, no changes (default) |
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
| File Type | Agent |
|---|---|
| *.ts, *.tsx | lang-typescript-expert |
| *.py | lang-python-expert |
| *.go | lang-golang-expert |
| *.kt | lang-kotlin-expert |
| *.java | lang-java-expert |
| *.rs | lang-rust-expert |
| Test files | qa-engineer |
| Docs, README | arch-documenter |
| Mixed | Multiple agents in parallel (R009) |
| Rule | Integration |
|---|---|
| R009 | Multiple file fixes execute in parallel |
| R010 | Orchestrator coordinates analysis and fix delegation |
| R015 | Full transparency on what improvements are suggested and why |
| R018 | 3+ fix agents → Agent Teams for coordination |
| worker-reviewer-pipeline | Can chain: auto-improve → worker-reviewer for critical fixes |
| pipeline-guards | Improvement count capped by guard limits |
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Pre-action boundary checking — validates agent tool calls against declared capabilities and task contracts
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Auto-detect project context and optimize harness — deactivate unused agents/skills, suggest missing experts, generate project profile
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Adversarial code review using attacker mindset — trust boundary, attack surface, business logic, and defense evaluation
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Apache Airflow best practices for DAG authoring, testing, and production deployment
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Alembic migration patterns for naming conventions, safety checks, expand-contract, env.py configuration, and CI integration
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Pre-routing ambiguity analysis — scores request clarity and asks clarifying questions when needed (inspired by ouroboros)
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