Review code for correctness, readability, performance, and security. The skill helps identify bugs and edge cases, explain why a change matters, and offer practical alternatives so feedback is clear and actionable.
Review code for quality, maintainability, and correctness
Run score Not tested
See how to installThis skill guides a review of code for correctness, maintainability, performance, and security. It helps check whether code behaves as expected, handles edge cases, and contains obvious bugs. It also considers whether variable and function names are clear and whether documentation is appropriate. Security checks include input validation, injection vulnerabilities, and secret management. Feedback should explain why a change is needed and offer an alternative, while also acknowledging good work.
Use it to look for issues in changed code or prepare clear, specific review comments for a team. It can also help keep review criteria consistent and communicate both improvements and positive aspects of the work.
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This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.
AI checked the SKILL.md for operations that need care and for setup requirements. The score comes only from actually running the skill (hands-on test).
Not counted in the score. Rated by AI (OpenAI Codex) as of Oct 28, 2026. Treat it as a guide and read the original before installing.
Review the instructions the agent will receive before you install.
This skill guides you through conducting thorough code reviews.
When reviewing code, consider:
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Write and revise FastMCP documentation pages with consistent structure, clear explanations, and runnable code examples. Covers accessibility, link and Python checks, and the publishing steps needed to confirm changes reach the live site.
Discover MCP servers and inspect their available tools from the command line, then invoke operations with typed arguments or JSON. Use local files, remote endpoints, or configured server names, and return structured output for scripts.
Build, extend, or review Python FastMCP servers using documentation for the installed version. Design operations that agents can discover and use, then check input definitions, results, error handling, and representative agent workflows.
Take a selected FastMCP bug from a reproducible failure to a focused fix. Check compatibility, run required validation, prepare a pull request, and follow automated checks and review feedback after publication.
Work with PDF documents by extracting their text, filling form fields, merging files in a chosen order, or splitting a PDF into separate pages. The skill describes these document handling tasks and points to API details in a reference file.
Write regression tests that catch recurring bugs in FastMCP changes using pytest. Covers reproducing failures before a fix, testing requests without a network server, and checking outgoing requests while replacing external services with test substitutes.