按技能名称、说明或 GitHub 作者匹配的结果。
Expert Python backend code reviewer that identifies over-complexity, duplicates, bad optimizations, and violations of best practices. Use when asked to review Python code quality, check for duplicate code, anal...
This skill should be used when the user asks to "review this code", "review PR", "code review", "review staged changes", "blast radius analysis", "check impact of changes", or needs comprehensive context-aware...
Comprehensive code review combining PR review, self-review, and quality checks. Supports reviewing PRs by number or comparing branches.
Implement static code analysis with linters, formatters, and security scanners to catch bugs early. Use when enforcing code standards, detecting security vulnerabilities, or automating code review.
Perform comprehensive code reviews with best practices, security checks, and constructive feedback. Use when reviewing pull requests, analyzing code quality, checking for security vulnerabilities, or providing...
Code review guidelines and checklist. Use when reviewing PRs or preparing code for review.
Use during verification phase when conducting thorough code reviews and providing constructive feedback based on universal software quality principles.
This skill should be used when the user asks to "review code", "review PR", "code review", "audit code", "check for bugs", "security review", "review my changes", "find issues in this code", "review the diff",...
Tactical code cleanup focusing on type strictness, single responsibility, fail-fast patterns, and DRY. Detects sloppy code, workarounds, silent failures, god classes, and duplication. Use for quick code quality...
Expert code review for quality, security, and maintainability. Use after writing or modifying code, or when user asks for review.
Systematic code review skill checking documentation quality and promoting code reuse
Universal code review - auto-detects scope from git changes, spec, commit, or brief
Provides comprehensive code review covering 6 focused aspects - architecture & design, code quality, security & dependencies, performance & scalability, testing coverage, and documentation & API design. Use thi...
Systematic and adaptable code review methodology using Language Server Protocol tools. Adapts to available LSP capabilities across programming languages. Use when user asks for code reviews, quality assessments...
Brutally honest code review in the style of Linus Torvalds, focusing on data structures, simplicity, and pragmatism. Use when you want critical, no-nonsense feedback that prioritizes engineering fundamentals ov...
Structured code review covering style, readability, and security concerns with actionable feedback. Use when reviewing pull requests or merge requests to identify issues and suggest improvements.
This skill should be used when the user asks to "review code", "code review", "check my code", "audit code", "find bugs", "security review", "performance review", or any ServiceNow code quality assessment.
Provides coding assistance with best practices and code review
Systematic code review skill checking documentation quality and promoting code reuse
Code review practices with technical rigor and verification gates. Use for receiving feedback, requesting code-reviewer subagent reviews, or preventing false completion claims in pull requests.
Systematic multi-perspective code review with consistent quality gates.
Comprehensive code review covering security vulnerabilities, performance bottlenecks, best practices, and refactoring opportunities. Use when user requests code review, security audit, or performance analysis.
Get Codex's code review of git changes after Claude makes edits. Trigger when user wants a second opinion on code changes ("have Codex review my changes", "get code review from Codex", "review this diff with Co...
Review Go code for adherence to Go Style Guide. Use when the user requests a code review of completed work, pull requests, or feature branches in Go projects. Focuses on critical bugs, race conditions, and impo...
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。