mastra-ai

performance-review

性能导向的代码审查技能,用于识别数据库查询、内存使用、渲染、API调用和算法复杂度等瓶颈和优化机会。

mastra-ai 29,040 3,039 更新于 8个月前

资源

1
GitHub

安装

npx skillscat add mastra-ai/mastra/performance-review

通过 SkillsCat registry 安装。

技能简介

性能导向的代码审查技能,用于识别数据库查询、内存使用、渲染、API调用和算法复杂度等瓶颈和优化机会。

SKILL.md

Performance Review

When reviewing code for performance issues, check each category below. Reference the detailed checklist in references/performance-checklist.md.

Database & Queries

  • N+1 query patterns (queries inside loops)
  • Missing database indexes for frequently queried fields
  • Unbounded queries without LIMIT/pagination
  • SELECT * instead of selecting only needed columns
  • Missing connection pooling

Memory & Resources

  • Memory leaks: event listeners not removed, intervals not cleared, growing caches without bounds
  • Large objects held in memory unnecessarily
  • Unbounded arrays or maps that grow with usage
  • Missing cleanup in component unmount/destroy lifecycle

Rendering (Frontend)

  • Unnecessary re-renders (missing React.memo, useMemo, useCallback where appropriate)
  • Large component trees re-rendering for small state changes
  • Missing virtualization for long lists
  • Synchronous heavy computation blocking the main thread
  • Large bundle sizes from unnecessary imports

API & Network

  • Missing caching for frequently accessed, rarely changing data
  • Sequential API calls that could be parallelized
  • Missing pagination for large data sets
  • Over-fetching data (requesting more than needed)
  • Missing request deduplication

Algorithmic Complexity

  • O(n²) or worse operations on potentially large datasets
  • Repeated computation that could be memoized
  • String concatenation in loops (use array join or template literals)
  • Unnecessary sorting or filtering passes

Severity Levels

  • 🔴 CRITICAL: Will cause performance degradation under normal load
  • 🟠 HIGH: Will cause issues at scale
  • 🟡 MEDIUM: Optimization opportunity with measurable impact
  • 🔵 LOW: Minor optimization suggestion