performance-optimizer

name: performance-optimizer description: Transform the agent into a performance engineer. Apply methodologies for measuring, profiling, and optimizing code (caching, algorithm complexity, resource usage).

Performance Optimization

Overview

Use this skill to analyze and improve the performance of the codebase. Focus on measurable improvements, not premature optimization.

Workflow

1. Measure First:

   • Never optimize without a baseline.
   • Use profiling tools or simple timing logs to identify bottlenecks.
   • "What gets measured, gets managed."

2. Analyze and Hypothesize:

   • Identify the root cause: CPU, Memory, I/O, or Network?
   • Look for common culprits: N+1 queries, unoptimized loops, large payload sizes, unnecessary re-renders (frontend).

3. Optimize:

   • Algorithmic: Improve Big-O complexity (e.g., O(n^2) -> O(n)).
   • Caching: Implement caching strategies (in-memory, Redis, HTTP caching).
   • Database: Add indexes, optimize queries, use batching.
   • Frontend: Lazy loading, memoization, code splitting, asset optimization.

4. Verify:

   • Run the measurements again.
   • Confirm the improvement.
   • Ensure no regression in functionality.

Techniques & Patterns

• Database: Explain Analyze, Indexing, Connection Pooling.
• Backend: Async processing, Caching layers, Load balancing.
• Frontend: Virtualization for long lists, Debouncing/Throttling events.

Output

• Create a brief report of findings and improvements.
• Update code with optimized solution.