code-review
Expert code reviewer for Python, TypeScript, and general best practices
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Expert code reviewer for Python, TypeScript, and general best practices
Code quality validation through linting, type checking, and build verification. Multi-language support for automated quality gates. Use when validating code quality: - After implementation to validate code meets standards - Before creating pull requests or commits - When debugging build/type/lint issues - User explicitly requests quality checks Provides language-specific tool commands and validation workflows for: - JavaScript/TypeScript (ESLint, tsc, build tools) - Python (Ruff, MyPy, Pyright) - Go (golangci-lint, go build) - Rust (Clippy, cargo check/build) - Java (Gradle, Maven) Focuses on detecting issues early through systematic automated checks. Keywords: lint, linting, type check, typecheck, build, quality, validation, eslint, tsc Do NOT load for: - Visual design work (use frontend-design-fundamentals, frontend-design-responsive) - UX patterns (use ux-feedback-patterns, ux-accessibility) - Initial development before implementation is stable - Figma extraction (use frontend-design-figma-extraction)
Review code changes for correctness, security, performance, and maintainability. Use for PR reviews, code audits, pre-merge checks, or quality validation of Laravel + React + Python code. EXCLUSIVE to reviewer agent.
Code quality validation through linting, type checking, and build verification. Multi-language support for automated quality gates. Use when validating code quality: - After implementation to validate code meets standards - Before creating pull requests or commits - When debugging build/type/lint issues - User explicitly requests quality checks Provides language-specific tool commands and validation workflows for: - JavaScript/TypeScript (ESLint, tsc, build tools) - Python (Ruff, MyPy, Pyright) - Go (golangci-lint, go build) - Rust (Clippy, cargo check/build) - Java (Gradle, Maven) Focuses on detecting issues early through systematic automated checks.
Executes the Python Refactoring Loop to improve code quality without changing behavior. Iterates through analysis, improvement, and verification using `python-verification` until all standards (SSOT, Ruff, Mypy) are met.
Enforces universal strict governance rules (500 lines, 5 funcs, 4 args) and interface-first I/O for Python, Golang, and .NET.
Python品質チェック。pytest/mypy/Black実行時に使用。「Pythonの品質チェック」「静的解析」で起動。
Review Python code changes with a focus on layered architecture boundaries, DI/DIP, configuration validation, typing quality (mypy/flake8 readiness), naming/docstring accuracy, and testability. Use when asked to “code review”, “PR review”, or “리뷰해줘” to prevent repeat feedback on architecture regressions and low-signal changes.
Python Enhancement Proposals (PEPs) and style guidelines
Advanced Python development with architecture expertise and automated code quality enforcement. Use when developing Python applications, libraries, or scripts that require high code quality, type safety, best practices, and professional architecture patterns. Includes automated linting with Ruff, type checking with MyPy, security scanning with Bandit, and comprehensive testing. Apply for tasks involving Python code creation, refactoring, quality checks, project initialization, or implementing design patterns.
Validate and auto-fix Python linting, formatting, and type issues using ruff and ty
Use when adding type hints, fixing type checker errors, working with Pydantic models. Triggers on "type", "types", "typing", "Pydantic", "BaseModel", "pyright", "basedpyright", "mypy", "type error", "type hint", "annotation", "Any", "dict", "list", "Optional", "Cannot assign", "Incompatible types", "Missing return type", "reportArgumentType", or when defining function signatures or data models.
Use when adding formatting, linting, and type checking to Python research code.
Python security patterns and OWASP vulnerability detection
Run Bandit security analysis to find common security issues and vulnerabilities in Python code. Use when the user mentions Bandit, security analysis, vulnerability scanning, security audit, software composition analysis (SCA), or wants to check for security issues in Python code.
Security best practices for Python development. Activated when working with security concerns, input validation, injection prevention, or threat modeling.
Validate AgentConfig definitions for the Agent Framework. Use when creating or modifying agent configurations to ensure correct structure, valid tool references, and proper sub-agent composition. Validates TypeScript interfaces and Python Pydantic models.
Authentication system design and implementation guidance with Python examples using strict typing. Use when: (1) Designing authentication flows (signup, login, logout, refresh), (2) Selecting between session vs token-based auth, (3) Designing JWT structure and claims, (4) Implementing OAuth 2.0 flows, (5) Setting up multi-service authentication patterns, (6) Creating password reset and email verification flows, (7) Implementing role-based access control (RBAC), (8) Creating security checklists for auth systems, (9) Planning frontend/backend auth integration. All examples follow Python typing standards and security best practices.