performance-optimization

Guidance for identifying bottlenecks, measuring impact, and making pragmatic performance improvements without cargo-cult optimization.

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SKILL.md

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Performance optimization

Core approach

  • Measure before and after when feasible.
  • Focus on actual bottlenecks and workload behavior.
  • Prefer clear changes with material impact over complex micro-optimizations.
  • Keep maintainability in view while improving performance.

Practical guidance

  • Consider data volume, latency, allocation, concurrency, rendering cost, query shape, and caching behavior where relevant.
  • Call out assumptions behind measurements and likely next bottlenecks.

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