9 Best Claude Skills for Performance Engineering
Compare Claude skills for caching, Web Vitals, bundles, React renders, load tests, cold starts, CPU profiles, memory leaks, and prompt caches.
Choose a Claude performance skill from measured evidence: cache-policy-designer for freshness and origin load, web-vitals-optimizer for real-user browser metrics, bundle-analyzer and react-render-profiler for frontend cost, load-test-designer for capacity, and flamegraph or memory skills for runtime bottlenecks.
Key takeaways
- Measure the user-visible or system-level bottleneck before changing code; plausible optimization is not evidence.
- Caching begins with correctness, ownership, variation, and invalidation—not a universal TTL.
- Field Web Vitals and representative production-like load matter more than isolated local benchmarks.
- CPU profiles, heap evidence, bundle reports, and render traces answer different performance questions.
- Re-measure the same workload after one targeted change and record regressions in cost, correctness, or resource use.
The best Claude performance skill depends on the evidence you have. A browser field metric, JavaScript bundle report, React trace, load-test curve, flamegraph, heap snapshot, and cold-start profile describe different systems. Asking Claude to “make it faster” before choosing the measurement invites speculative edits.
| Skill | Best for | Evidence | Main result |
|---|---|---|---|
| cache-policy-designer | Freshness and origin load | Data flow and cache behavior | Layered cache policy |
| web-vitals-optimizer | LCP, CLS, and INP | RUM/CrUX plus trace | Targeted browser fix |
| bundle-analyzer | Client JavaScript size | Build artifact report | Ranked size reductions |
| react-render-profiler | Wasteful UI renders | React profiler trace | Render-path fix |
| load-test-designer | Throughput and saturation | Representative workload | Load-test plan |
| cold-start-optimizer | Startup latency | Phase timing | Startup improvements |
| flamegraph-analyzer | CPU time | CPU profile | Hot-path diagnosis |
| memory-leak-hunter | Growing memory | Heap snapshots | Retention-path diagnosis |
| prompt-cache-optimizer | LLM prefix reuse | Token and latency data | Prompt-cache strategy |
1. cache-policy-designer: make caching correct
cache-policy-designer inventories the authoritative data, all cache layers, key dimensions, privacy boundary, freshness tolerance, invalidation events, stampede behavior, and outage semantics. It distinguishes browser or CDN headers from application and data caches instead of applying one TTL everywhere.
Use it before adding a cache and when users report stale or cross-tenant responses.
2. web-vitals-optimizer: improve real-user experience
web-vitals-optimizer anchors on p75 field LCP, CLS, and INP. It uses lab tooling to identify the element, shift, or long task responsible, applies one targeted change, and verifies the mechanism immediately while field data accumulates.
3. bundle-analyzer: find shipped JavaScript cost
bundle-analyzer measures built chunks, duplication, eager imports, large dependencies, polyfills, and route boundaries. It ranks reductions by bytes and user reach rather than recommending package removal without checking use.
4. react-render-profiler: explain render work
react-render-profiler reads commit and component timing, prop or state changes, context fan-out, repeated calculations, and list behavior. It avoids reflexive memoization when the render is cheap or the dependency comparison costs more.
5. load-test-designer: find the capacity curve
load-test-designer models arrival rate, concurrency, user journeys, data variation, ramp, steady state, spikes, and recovery. It defines latency percentiles, error rate, throughput, saturation, and resource signals, then separates generator limits from system limits.
6. cold-start-optimizer: shorten initialization
cold-start-optimizer decomposes startup into platform allocation, runtime bootstrap, imports, configuration, network connections, and application initialization. Optimize the dominant phase and check whether warm performance or correctness regresses.
7. flamegraph-analyzer: fix the widest CPU path
flamegraph-analyzer interprets width as sampled CPU time, follows stacks to the widest actionable leaf, and distinguishes useful work from framework, serialization, allocation, or lock overhead. Capture a representative workload before reading the graph.
8. memory-leak-hunter: locate retained growth
memory-leak-hunter compares heap snapshots or allocation profiles across repeated cycles, identifies growing object classes, and traces retaining paths to roots. A high heap at one moment is not enough; a leak requires retained growth under a controlled workload.
9. prompt-cache-optimizer: reuse stable LLM prefixes
prompt-cache-optimizer organizes stable instructions and reference context ahead of variable conversation content so provider caching can reuse prefix computation. It measures hit rate, cached tokens, latency, and cost without changing prompt behavior blindly.
Recommended performance stack
For a web application, combine field experience, shipped code, runtime capacity, and cache correctness:
npx agentscamp add skills/web-vitals-optimizer
npx agentscamp add skills/bundle-analyzer
npx agentscamp add skills/load-test-designer
npx agentscamp add skills/cache-policy-designerEvery optimization report should state the baseline, workload, bottleneck evidence, exact change, post-change measurement, and tradeoffs. Without a comparable before-and-after result, the change is only a theory.
Continue exploring
- 9 Best Claude Skills for Frontend Development — Compare Claude skills for accessibility, Web Vitals, React renders, bundles, localization, browser security, test data, tests, and caching.
Frequently asked questions
- Which Claude performance skill should I use first?
- Start from the symptom and measurement. Use web-vitals-optimizer for field LCP, CLS, or INP; load-test-designer for capacity; flamegraph-analyzer for CPU; memory-leak-hunter for heap growth; and cache-policy-designer for repeated origin work or stale responses.
- Can cache-policy-designer fix stale data?
- It maps layers, keys, writers, freshness bounds, and invalidation events to identify the correctness gap. Implementation should follow only after unknown writers and identity variation are resolved.
- Is Lighthouse enough for web performance?
- No. Lighthouse is useful diagnostic lab data. Core Web Vitals decisions should anchor on p75 field data from real users, with RUM providing faster verification after a change.
- Should performance skills optimize code automatically?
- Only after a baseline and bottleneck are proven. Make one scoped change, preserve behavior, rerun the same workload, and compare latency, throughput, resource use, and cost.
Related
- 9 Best Claude Skills for Frontend DevelopmentCompare Claude skills for accessibility, Web Vitals, React renders, bundles, localization, browser security, test data, tests, and caching.
- Cache Policy DesignerDesign a cache policy from data ownership, freshness, privacy, invalidation, and failure requirements across browser, CDN, reverse-proxy, application, and data caches. Use when adding caching, debugging stale responses, reviewing Cache-Control behavior, reducing origin load, or deciding whether a value can be cached safely at all.
- Load Test DesignerDesign a defensible load test — a realistic workload model, a deliberate test type, and SLO-tied pass/fail thresholds — instead of a meaningless tight-loop script that hammers one endpoint. Use when validating capacity or SLOs before a launch or scaling event, when sizing infrastructure, or when an existing load test reports averages that nobody trusts.
- Web Vitals OptimizerDiagnose and fix Core Web Vitals — LCP, CLS, and INP — by treating real-user field data at p75 as the source of truth, using Lighthouse/WebPageTest only to find the at-fault element, script, or shift, then applying the one targeted fix per metric and re-measuring. Use when a page feels slow, scores poorly on PageSpeed/Lighthouse, or fails CWV in CrUX/RUM field data.
- Flamegraph AnalyzerTurn a CPU profile or flamegraph into a concrete optimization instead of guessing where the time goes: capture under a realistic workload with a sampling profiler, read the graph correctly (width = time, depth ≠ time), find the widest self-time leaves, ask if that work is necessary/redundant/algorithmically wrong, fix the biggest contributor, then re-profile. Use when code is CPU-bound and slow, a function is hot but you don't know which part, or you have a profile you can't interpret.
- Memory Leak HunterFind and fix a memory leak in a running app: confirm it's a real leak under steady load, diff two heap snapshots to name the growing object and its retention path, cut the root reference that blocks collection, and re-run to confirm memory plateaus. Use when RSS climbs until OOM/restart, heap grows unbounded across a steady workload, or GC pauses worsen the longer the process runs.