Agent Skills: Performance Review

Performance-focused code review for identifying bottlenecks and optimization opportunities

UncategorizedID: mastra-ai/mastra/performance-review

Repository

mastra-aiLicense: NOASSERTION
22,3231,790

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pnpm dlx add-skill https://github.com/mastra-ai/mastra/tree/HEAD/templates/template-github-review-agent/workspace/skills/performance-review

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templates/template-github-review-agent/workspace/skills/performance-review/SKILL.md

Skill Metadata

Name
performance-review
Description
Performance-focused code review for identifying bottlenecks and optimization opportunities

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(nΒ²) 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

  • πŸ”΄ CRITICAL: Will cause performance degradation under normal load
  • 🟠 HIGH: Will cause issues at scale
  • 🟑 MEDIUM: Optimization opportunity with measurable impact
  • πŸ”΅ LOW: Minor optimization suggestion