AI-optimized browser automation CLI with context-efficient snapshots. Use for long autonomous sessions, self-verifying workflows, video recording, and cloud browser testing (Browserbase).
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Review code quality, receive feedback with technical rigor, verify completion claims. Use before PRs, after implementing features, when claiming task completion. Includes scout-based edge case detection and native Task pipeline orchestration.
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Guide proper code review practices emphasizing technical rigor, evidence-based claims, and verification over performative responses.
If invoked with context (recent changes/PR), proceed with review. If invoked WITHOUT arguments, ask the user to choose available review operations:
| Operation | Description |
|---|---|
(default) | Review recent changes/PR |
codebase | Full codebase scan & analysis |
codebase parallel | Parallel multi-reviewer audit |
Present options with header "Review Operation", question "What would you like to do?".
YAGNI, KISS, DRY always. Technical correctness over social comfort. Be honest, be brutal, straight to the point, and be concise.
Verify before implementing. Ask before assuming. Evidence before claims.
| Practice | When | Reference |
|---|---|---|
| Receiving feedback | Unclear feedback, external reviewers, needs prioritization | references/code-review-reception.md |
| Requesting review | After tasks, before merge, stuck on problem | references/requesting-code-review.md |
| Verification gates | Before any completion claim, commit, PR | references/verification-before-completion.md |
| Edge case scouting | After implementation, before review | references/edge-case-scouting.md |
| Task-managed reviews | Multi-file features (3+ files), parallel reviewers, fix cycles | references/task-management-reviews.md |
SITUATION?
│
├─ Received feedback → STOP if unclear, verify if external, implement if human partner
├─ Completed work → Scout edge cases → Request code_reviewer subagent
├─ Multi-file feature (3+ files) → Create review pipeline tasks (scout→review→fix→verify)
└─ About to claim status → RUN verification command FIRST
Pattern: READ → UNDERSTAND → VERIFY → EVALUATE → RESPOND → IMPLEMENT
Rules:
Source handling:
Full protocol: references/code-review-reception.md
When: After each task, major features, before merge
Process:
BASE_SHA=$(git rev-parse HEAD~1) and HEAD_SHA=$(git rev-parse HEAD)Full protocol: references/requesting-code-review.md
When: After implementation, before requesting code_reviewer
Process:
$scout with edge-case-focused promptFull protocol: references/edge-case-scouting.md
When: Multi-file features (3+ changed files), parallel code_reviewer scopes, review cycles with Critical fix iterations.
Pipeline: scout → review → fix → verify (each a Task with dependency chain)
tracked task creation: "Scout edge cases" → pending
tracked task creation: "Review implementation" → pending, blockedBy: [scout]
tracked task creation: "Fix critical issues" → pending, blockedBy: [review]
tracked task creation: "Verify fixes pass" → pending, blockedBy: [fix]
Parallel reviews: Spawn scoped code_reviewer subagents for independent file groups (e.g., backend + frontend). Fix task blocks on all reviewers completing.
Re-review cycles: If fixes introduce new issues, create cycle-2 review task. Limit 3 cycles, escalate to user after.
Full protocol: references/task-management-reviews.md
Iron Law: NO COMPLETION CLAIMS WITHOUT FRESH VERIFICATION EVIDENCE
Gate: IDENTIFY command → RUN full → READ output → VERIFY confirms → THEN claim
Requirements:
Red Flags: "should"/"probably"/"seems to", satisfaction before verification, trusting agent reports
Full protocol: references/verification-before-completion.md
| Subcommand | Reference | Purpose |
|---|---|---|
$code-review codebase | references/codebase-scan-workflow.md | Scan & analyze the codebase |
$code-review codebase parallel | references/parallel-review-workflow.md | Ultrathink edge cases, then parallel verify |
Verify. Scout. Question. Then implement. Evidence. Then claim.
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AI-optimized browser automation CLI with context-efficient snapshots. Use for long autonomous sessions, self-verifying workflows, video recording, and cloud browser testing (Browserbase).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Generate images via Nano Banana with 129 curated prompts. Mandatory validation interview refines style/mood/colors (use --skip to bypass). 3 modes: search, creative, wild. Styles: Ukiyo-e, Bento grid, cyberpunk, cinematic, vintage patent.
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Analyze images/audio/video with Gemini API (better vision than Codex). Generate images (Imagen 4), videos (Veo 3). Use for vision analysis, transcription, OCR, design extraction, multimodal AI.
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Answer technical and architectural questions with expert consultation.
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Build backends with Node.js, Python, Go (NestJS, FastAPI, Django). Use for REST/GraphQL/gRPC APIs, auth (OAuth, JWT), databases, microservices, security (OWASP), Docker/K8s.
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Add authentication with Better Auth (TypeScript). Use for email/password, OAuth providers (Google, GitHub), 2FA/MFA, passkeys/WebAuthn, sessions, RBAC, rate limiting.
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