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These are idiomatic FastAPI patterns that may appear problematic but are correct:

Structured code review for security, performance, correctness, and maintainability across PR diffs and file changes. \n \n Audits security risks including SQL injection, XSS, CSRF, authentication flaws, and credential exposure \n Identifies performance issues like N+1 queries, memory leaks, algorithmic complexity, and resource leaks \n Checks correctness for edge cases, race conditions, error handling, and type safety gaps \n Works standalone with diffs and file paths; integrates with source con

Simple, pragmatic, opinionated. Only what matters for writing production-grade PostgreSQL queries.

Simple, pragmatic, opinionated. Only what matters for writing production-grade SQLAlchemy and Alembic code.

Modern Python tooling, naming conventions, type checking, and documentation standards for maintainable codebases. \n \n Configure ruff for unified linting and formatting, replacing flake8, isort, and black with a single fast tool \n Set up strict type checking with mypy or pyright to catch errors before runtime \n Follow PEP 8 naming conventions: snake_case for functions/variables, PascalCase for classes, SCREAMING_SNAKE_CASE for constants \n Write Google-style docstrings for all public APIs wit

Code Components: Custom React components added to canvas. Support addPropertyControls.

Expert code review of git changes with focus on SOLID violations, security risks, and actionable improvements. \n \n Analyzes current git diff for SOLID principle violations, architecture smells, and removal candidates using structured checklists \n Scans for security risks including injection, authentication gaps, race conditions, and unsafe deserialization with exploitability assessment \n Flags code quality issues: error handling gaps, N+1 queries, boundary condition bugs, and performance hot

When explaining code, always include: \n \n Start with an analogy : Compare the code to something from everyday life \n Draw a diagram : Use ASCII art to show the flow, structure, or relationships \n Walk through the code : Explain step-by-step what happens \n Highlight a gotcha : What's a common mistake or misconception? \n \n Keep explanations conversational. For complex concepts, use multiple analogies.

Production-grade code standards emphasizing correctness, crash-safety, and Rust idioms over convenience. \n \n Prioritizes data integrity: crash on invalid state rather than corrupt data; assert invariants aggressively; handle all errors explicitly \n Rust-specific patterns: make illegal states unrepresentable, use exhaustive pattern matching and enums over strings, minimize allocations \n Comments document why , not what ; avoid temporal markers, AI conversation references, and code-repeating e

Find unused functions and dead code using TLDR static analysis.