htlin222/perf
claude.symlink/skills/perf/SKILL.md
Profile applications, optimize bottlenecks, and implement caching. Use for performance issues or optimization tasks.
$ install --global
skillsauthnpx skillsauth add htlin222/dotfiles perfInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 5, 2026, 8:06 PM6.7s1 file scanned
SKILL.md
- name:
- perf
- description:
- Profile applications, optimize bottlenecks, and implement caching. Use for performance issues or optimization tasks.
Performance Engineering
Profile, analyze, and optimize application performance.
When to Use
- Application is slow or unresponsive
- User reports performance issues
- Before scaling infrastructure
- Optimizing critical paths
- Setting up monitoring
Optimization Process
- Measure - Profile before optimizing
- Identify - Find the biggest bottlenecks
- Optimize - Fix highest-impact issues first
- Verify - Confirm improvements with metrics
Profiling Commands
# Node.js profiling
node --prof app.js
node --prof-process isolate-*.log > profile.txt
# Python profiling
python -m cProfile -o output.prof script.py
python -m pstats output.prof
# Go profiling
go tool pprof http://localhost:6060/debug/pprof/profile
Common Bottlenecks
Database
- Missing indexes (add indexes on WHERE/JOIN columns)
- N+1 queries (use eager loading)
- Large result sets (add pagination)
Memory
- Memory leaks (check event listeners, closures)
- Large objects (stream instead of buffer)
- Cache without TTL (add expiration)
CPU
- Synchronous operations (make async)
- Complex algorithms (optimize or cache)
- Unnecessary computation (memoize)
Network
- Too many requests (batch/combine)
- Large payloads (compress, paginate)
- No caching (add CDN, browser cache)
Performance Budgets
| Metric | Target | | -------------- | ------ | | Load Time (3G) | <3s | | Load Time (4G) | <1s | | API Response | <200ms | | Bundle Size | <500KB | | LCP | <2.5s | | FID | <100ms | | CLS | <0.1 |
Output Format
## Performance Report
**Before:** [baseline metrics]
**After:** [improved metrics]
**Improvement:** [percentage]
### Bottlenecks Identified
1. [Issue] - Impact: High/Medium/Low
### Optimizations Applied
1. [Change] → [Result]
Examples
Input: "The API is slow" Action: Profile endpoints, identify slow queries, optimize, verify improvement
Input: "Page load is taking too long" Action: Analyze bundle, check network, optimize critical path, add caching
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