Total 43,182 skills, Code Quality has 2020 skills
Showing 12 of 2020 skills
Python error handling patterns including input validation, exception hierarchies, and partial failure handling. Use when implementing validation logic, designing exception strategies, handling batch processing failures, or building robust APIs.
Use this skill when writing code, implementing features, refactoring, planning architecture, designing systems, reviewing code, or debugging. This skill transforms junior-level code into senior-engineer quality software through SOLID principles, TDD, clean code practices, and professional software design.
Profile application performance, identify bottlenecks, and optimize hot paths using CPU profiling, flame graphs, and benchmarking. Use when investigating performance issues or optimizing critical code paths.
All changes to code must follow the guidance documented in the repository. Before any issue is filed, branch is made, commits generated, or pull request (or PR) created, a search must be done to ensure the right steps are followed. Whenever asked to create an issue, commit messages, to push code, or create a PR, use this skill so everything is done correctly.
Review code for logging patterns and suggest evlog adoption. Detects console.log spam, unstructured errors, and missing context. Guides wide event design, structured error handling, request-scoped logging, and log draining with adapters (Axiom, OTLP).
Review a project's PRs to check for issues detected in code review by Seer Bug Prediction. Use when asked to review or fix issues identified by Sentry in PR comments, or to find recent PRs with Sentry feedback.
Profile CPU usage to identify hot spots and bottlenecks. Optimize code paths consuming most CPU time for better performance and resource efficiency.
Simplify and refine recently modified code for clarity and consistency. Use after writing code to improve readability without changing functionality.
Runs external LLM code reviews (OpenAI Codex or Google Gemini CLI) on uncommitted changes, branch diffs, or specific commits. Use when the user asks for a second opinion, external review, codex review, gemini review, or mentions /second-opinion.
Common Python anti-patterns to avoid. Use as a checklist when reviewing code, before finalizing implementations, or when debugging issues that might stem from known bad practices.
Master ShellCheck static analysis configuration and usage for shell script quality. Use when setting up linting infrastructure, fixing code issues, or ensuring script portability.
Daily coding assistant that auto-triggers when writing/modifying code, providing a core checklist. ✅ Trigger scenarios: - Implementing new features, adding code, modifying existing code - User requests "write a...", "implement...", "add...", "modify..." - Any coding task involving Edit/Write tools ❌ Does not trigger: - Pure reading/understanding code (no modification intent) - Already covered by specialized skills (bug-detective, architecture-design, tdd-guide) - Configuration file changes, documentation writing