Pre-action boundary checking — validates agent tool calls against declared capabilities and task contracts
中文简介正在准备中。当前显示原文说明。
Opt-in post-PR analysis and improvement suggestions for code quality enhancement
中文简介正在准备中。当前显示原文说明。
查看安装方法安装前可以查看交给 AI 代理的指令内容。
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| Documentation | Missing JSDoc for public APIs, outdated README refs |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
中文简介正在准备中。当前显示原文说明。
Auto-detect project context and optimize harness — deactivate unused agents/skills, suggest missing experts, generate project profile
中文简介正在准备中。当前显示原文说明。
Adversarial code review using attacker mindset — trust boundary, attack surface, business logic, and defense evaluation
中文简介正在准备中。当前显示原文说明。
Apache Airflow best practices for DAG authoring, testing, and production deployment
中文简介正在准备中。当前显示原文说明。
Alembic migration patterns for naming conventions, safety checks, expand-contract, env.py configuration, and CI integration
中文简介正在准备中。当前显示原文说明。
Pre-routing ambiguity analysis — scores request clarity and asks clarifying questions when needed (inspired by ouroboros)
中文简介正在准备中。当前显示原文说明。