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Code review practices emphasizing technical rigor, evidence-based claims, and verification. Use when receiving code review feedback, completing tasks requiring review, or before making completion claims.
| name | code-review |
| description | Code review practices emphasizing technical rigor, evidence-based claims, and verification. Use when receiving code review feedback, completing tasks requiring review, or before making completion claims. |
| license | MIT |
Guide proper code review practices emphasizing technical rigor, evidence-based claims, and verification over performative responses.
Code review requires three distinct practices:
Technical correctness over social comfort. Verify before implementing. Ask before assuming. Evidence before claims.
SITUATION?
│
├─ Received feedback
│ ├─ Unclear items? → STOP, ask for clarification first
│ ├─ From human partner? → Understand, then implement
│ └─ From external reviewer? → Verify technically before implementing
│
├─ Completed work
│ ├─ Major feature/task? → Request systematic review
│ └─ Before merge? → Request systematic review
│
└─ About to claim status
├─ Have fresh verification? → State claim WITH evidence
└─ No fresh verification? → RUN verification command first
Before any completion claim or commit:
For detailed protocols, see:
references/receiving-feedback.md - How to handle code review feedbackreferences/requesting-review.md - Systematic review processesreferences/verification-gates.md - Evidence before claims protocolManage Git commits using conventional commit format with atomic staging. Always generate plain git commands before running them and offer to let the user run them manually.
Create AGENTS.md files for project-specific inline rules. Use when adding small, project-specific instructions that should be committed in repos.
Media processing utilities for images, audio, and video using FFmpeg and ImageMagick. Use when working with media conversion, optimization, or batch processing tasks.
Core software engineering principles for code style, documentation, and development workflow. Applies when editing code, working in software repositories, or performing software development tasks.
Python development guidelines and best practices. Use when working with Python code.
Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems.