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Measure-first performance optimization that balances gains against complexity. Use when addressing slow code, profiling issues, or evaluating optimization trade-offs.
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SOC 職業分類に基づく
| name | optimizing-performance |
| description | Measure-first performance optimization that balances gains against complexity. Use when addressing slow code, profiling issues, or evaluating optimization trade-offs. |
| argument-hint | [file-path-or-area] |
Core principle: Readable code that's "fast enough" beats complex code that's "optimal". Measure first.
Focus area: If $ARGUMENTS is provided, use it as the optimization target. Otherwise, run git diff and focus on unstaged changes. If no unstaged changes exist, ask the user what to optimize.
IF optimization reduces complexity AND improves performance → ALWAYS DO IT
IF optimization increases complexity → Only if 10x faster OR fixes critical UX (>16ms UI, >100ms input)
Multiple loops → Single loop:
// ❌ Three passes
const ids = users.map(u => u.id);
const active = users.filter(u => u.active);
// ✅ One pass
const { ids, active } = users.reduce((acc, u) => {
acc.ids.push(u.id);
if (u.active) acc.active.push(u);
return acc;
}, { ids: [], active: [] });
Nested loops → Hash map (O(n²) → O(n)):
// ❌ O(n²)
const matched = orders.filter(o => users.some(u => u.id === o.userId));
// ✅ O(n)
const userIds = new Set(users.map(u => u.id));
const matched = orders.filter(o => userIds.has(o.userId));
| Pattern | When | Fix |
|---|---|---|
| Virtualization | Lists >1000 items | react-window, tanstack-virtual |
| Memoization | >5ms calc OR unnecessary re-renders | useMemo, React.memo |
| Batching | Multiple state updates | Single setState, bulk INSERT |
| Lazy loading | Large dependencies | import('./heavy-lib') |
Writing style and tone guide for human-sounding content. Use when writing documentation, READMEs, commit messages, PR descriptions, blog posts, LinkedIn posts, social media content, or any user-facing content.
Executes implementation plans with smart task grouping. Groups related tasks to share context, parallelizes across independent subsystems.
Diagnose and fix tests that pass in isolation but fail when run concurrently. Covers shared state isolation, resource conflicts, and timing-based flakiness.
Guides CI/CD pipeline architecture, security hardening, and deployment strategies for GitHub Actions. Use when designing workflows, securing supply chains, optimizing build performance, configuring deployments, managing infrastructure as code pipelines, or setting up pipeline observability.
Defines product features from a PM perspective before technical planning begins. Use when scoping new features, writing product specs, defining user problems, choosing what to build, researching existing patterns, or bridging the gap between strategy and implementation. Covers JTBD analysis, competitive research, UX/DX experience definition, and scope negotiation for consumer, B2B, and developer tool products.
Writes behavior-focused tests using Testing Trophy model with real dependencies. Use when writing tests, choosing test types, or avoiding anti-patterns like testing mocks.