Automated summary
Provides guidance on performance optimization including profiling (CPU, memory, I/O), caching layers (CDN, application, database), connection pooling, lazy loading, code splitting, database query optimization, and load balancing.
Strengths
- Structured six-step process that avoids premature optimization
- Covers multiple areas (frontend, backend, databases, scaling)
- Detailed references for specific techniques (caching, SQL, profiling)
- Includes common anti-patterns to avoid frequent mistakes
Limitations
- Requires profiling data to be effective
- May be complex for beginners without optimization experience
- Optimizations are highly context-dependent
Use this skill when diagnosing performance issues, optimizing response times, or designing for scale.
Do not use for premature optimization without evidence of a bottleneck, or for quick fixes without prior measurement.
Security analysis
SafeThe skill provides a safe, high-level performance optimization guide. It does not instruct destructive actions, exfiltration, or obfuscated payloads. Use of Bash is for legitimate profiling, not malicious commands.
No concerns found
How this analysis is madeExamples
Profile the CPU usage of my Node.js server under realistic load and identify the main bottleneck. Follow the performance optimization process: first measure baseline, then use clinic.js to generate a flame graph, and suggest optimizations only for the hottest code path.I have a slow PostgreSQL query. Run EXPLAIN ANALYZE on it and identify why it's slow. Suggest index changes or query rewrites to reduce execution time. After implementing, re-run the analysis to verify improvement.My web page's Largest Contentful Paint (LCP) is 4 seconds. Analyze the frontend bundle with Lighthouse, identify the largest blocking resources, and suggest code splitting or image optimization strategies. Verify improvement with a second measurement.name: performance-optimization description: Guides on performance including profiling (CPU, memory, I/O), caching layers (CDN, application, database), connection pooling, lazy loading, code splitting, database query optimization, and load balancing. Use when diagnosing performance issues, optimizing response times, or designing for scale. allowed-tools: Read, Grep, Glob, Bash
You are a performance optimization specialist informed by the Software Engineer by RN competency matrix. Always measure before and after optimizing. Never optimize without profiling data.
Optimization Process
- Define goals: Set measurable targets (p99 latency < 200ms, throughput > 5000 RPS, LCP < 2.5s)
- Measure baseline: Establish current performance with profiling under realistic load
- Identify bottleneck: Use profiling tools to find the actual bottleneck (CPU, memory, I/O, network, lock contention)
- Optimize: Implement the fix for the identified bottleneck only
- Verify: Re-run the same measurements, confirm improvement, check for regressions
- Document: Record what was changed, why, and the measured impact
Common Anti-Patterns
- Premature optimization without profiling data
- Optimizing code that runs once instead of hot paths
- Adding caching without understanding invalidation requirements
- Over-indexing databases (write penalty exceeds read benefit)
When to Load References
CDN headers, Redis cache-aside, in-memory caches, cache invalidation strategies:
Load references/caching.md — Cache-Control headers, Caffeine/ristretto/lru-cache, stampede prevention.
EXPLAIN ANALYZE, index types, slow queries, connection pooling:
Load references/database-query.md — PostgreSQL/MySQL query plans, index selection, PgBouncer, HikariCP.
Core Web Vitals, bundle splitting, image formats, network protocols:
Load references/frontend-performance.md — LCP/INP/CLS optimization, code splitting patterns, Brotli/gzip.
CPU/memory profiling, flame graphs, benchmarking tools:
Load references/backend-profiling.md — clinic.js, py-spy, async-profiler, pprof, k6, memory leak detection.
Load balancing algorithms, circuit breakers, rate limiting, auto-scaling:
Load references/scaling-load-balancing.md — HPA, KEDA, AWS target tracking, goroutines, virtual threads.
From the file to a first result
The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.
View the source and supporting filesThis download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.
1. Download the file
Download SKILL.mdFrom the root of a test project, save the file as .skill-downloads/performance-optimization-mm8o5287/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.
Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.
mkdir -p '.skill-downloads/performance-optimization-mm8o5287' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/performance-optimization-mm8o5287/download' --output '.skill-downloads/performance-optimization-mm8o5287/SKILL.md.part' && mv '.skill-downloads/performance-optimization-mm8o5287/SKILL.md.part' '.skill-downloads/performance-optimization-mm8o5287/SKILL.md'2. Check prerequisites
Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.
Tools declared by the author (check availability in your agent): Read, Grep, Glob, Bash
No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.
The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.
3. Load the skill
After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.
Claude Code
test -f '.skill-downloads/performance-optimization-mm8o5287/SKILL.md' && test -s '.skill-downloads/performance-optimization-mm8o5287/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/performance-optimization' && cp -R '.skill-downloads/performance-optimization-mm8o5287' '.claude/skills/performance-optimization'OpenSkills
OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.
Official OpenSkills installationopenskills install './.skill-downloads/performance-optimization-mm8o5287'openskills read 'performance-optimization-mm8o5287'Reading should display the installed file content and its base directory. It does not run the skill or install its dependencies.
For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.
openskills syncManual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.
4. Try a first task
Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:
Read .skill-downloads/performance-optimization-mm8o5287/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.
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