Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/cwinvestments/memstack/performance-auditnpx skills add cwinvestments/memstack --skill performance-auditgit clone --depth 1 https://github.com/cwinvestments/memstackWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00069 | $0.04386 |
| Opus 5 | $0.00034 | $0.02193 |
| Sonnet 5 | $0.00014 | $0.00877 |
| Haiku 4.5 | $0.00007 | $0.00439 |
Grade A, and why
memstack-development-performance-audit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 486 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🚀 Performance Audit — Full-Stack Performance Scanner
Identify and prioritize performance bottlenecks across frontend, backend, and network layers with measured impact and fix priority.
Activation
When this skill activates, output:
🚀 Performance Audit — Scanning for performance bottlenecks...
| Context | Status |
|---|---|
| User says "performance audit", "optimize", "slow app" | ACTIVE |
| User mentions bundle size, N+1 queries, or Core Web Vitals | ACTIVE |
| User wants to find memory leaks or unnecessary re-renders | ACTIVE |
| User wants database schema optimization specifically | DORMANT — see database-architect |
| User wants API design review (not performance) | DORMANT — see api-designer |
| User wants general code quality review | DORMANT — see code-reviewer |
Protocol
Step 1: Gather Inputs
Ask the user for:
- Stack: Frontend framework, backend language, database?
- Symptoms: What feels slow? (initial load, interactions, API responses, builds)
- Scale: How many users? How much data?
- Metrics: Any existing performance data? (Lighthouse scores, APM dashboards)
- Priority: User-facing speed or server-side efficiency?
Step 2: Frontend — Bundle Analysis
Check bundle size and composition:
# Next.js
npx @next/bundle-analyzer
# or: ANALYZE=true next build
# Webpack (generic)
npx webpack-bundle-analyzer stats.json
# Vite
npx vite-bundle-visualizer
What to look for:
| Issue | Detection | Impact | Fix |
|---|---|---|---|
| Large dependencies | Bundle > 200KB gzipped | Slow initial load | Replace with lighter alternatives |
| Duplicate packages | Same lib in multiple versions | Wasted bytes | Dedupe or pin single version |
| Unused exports | Tree-shaking not working | Wasted bytes | Use ESM imports, avoid barrel files |
| No code splitting | Single large bundle | Slow initial load | Dynamic imports, route-based splitting |
| Unoptimized images | Images > 100KB without optimization | Slow load | next/image, sharp, WebP/AVIF |
| Missing compression | No gzip/brotli on responses | 60-80% larger payloads | Enable in server/CDN config |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 486 lines · 69 tokens per session scan A df4f75b40947
memstack-development-performance-audit is a skill published in the GitHub repository cwinvestments/memstack (417 stars, last pushed 5d ago), licensed MIT. It adds 69 tokens to every session and 4,386 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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