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From optimize
Analyzes runtime performance bottlenecks in code, applies targeted optimizations by impact order, and measures before/after improvements with metrics.
How this command is triggered — by the user, by Claude, or both
Slash command
/optimize:optimize-perfThe summary Claude sees in its command listing — used to decide when to auto-load this command
Analyze and optimize code for runtime performance with measurable improvements. ## Steps 1. Identify the performance target: 2. Profile the code: 3. Analyze common performance issues: 4. Apply optimizations in order of impact: 5. Measure the improvement after each optimization. 6. Document the trade-offs of each optimization. ## Format ## Rules - Always measure before and after; never optimize without data. - Fix the biggest bottleneck first (Amdahl's Law). - Do not sacrifice readability for marginal gains.
Analyze and optimize code for runtime performance with measurable improvements.
Target: <what was optimized>
Before: <baseline metric>
After: <improved metric>
Improvement: <percentage>
5plugins reuse this command
First indexed Mar 30, 2026
npx claudepluginhub smarks26/awesome-claude-code-toolkit --plugin optimize/optimize-perfAnalyzes runtime performance bottlenecks in code, applies targeted optimizations by impact order, and measures before/after improvements with metrics.
/optimizeAnalyzes code for performance bottlenecks and presents three specific optimization recommendations with supporting rationale.
/optimize-codeAnalyze algorithms and choose optimal implementation for performance.
/optimizeCoordinates a team of four optimization experts to analyze performance bottlenecks, design optimization strategies, and produce a quantified improvement plan.
/optimizeOptimizes performance of <PERFORMANCE_TARGET> via bottleneck analysis, expert-coordinated strategies for algorithms/resources/scalability, and outputs plans with benchmarks/monitoring.
/perf-profileProfiles slow code paths, captures CPU/I/O/memory profiles under representative load, identifies top bottlenecks by self-time, and suggests prioritized fixes with estimated speedups.