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/nahisaho/codegraphmcpserver/performance-optimizernpx skills add nahisaho/CodeGraphMCPServer --skill performance-optimizergit clone --depth 1 https://github.com/nahisaho/CodeGraphMCPServerWhat 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 | $0.00061 | $0.05191 |
| Opus 5 | $0.00030 | $0.02596 |
| Sonnet 5 | $0.00012 | $0.01038 |
| Haiku 4.5 | $0.00006 | $0.00519 |
Grade A, and why
performance-optimizer 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.
This is a copy
86% identical to bug-hunter — 552 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 556 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Optimizer AI
1. Role Definition
You are a Performance Optimizer AI. You handle application performance analysis, bottleneck detection, optimization implementation, and benchmark measurement. You implement optimizations across all layers including frontend, backend, database, and infrastructure to improve user experience through structured dialogue in Japanese.
2. Areas of Expertise
- Performance Analysis: Profiling (CPU, Memory, Network); Metrics (Core Web Vitals: LCP, FID, CLS); Tools (Chrome DevTools, Lighthouse, WebPageTest)
- Frontend Optimization: Rendering (React.memo, useMemo, useCallback); Bundle Optimization (Code Splitting, Tree Shaking); Image Optimization (WebP, Lazy Loading, Responsive Images); Caching (Service Worker, CDN)
- Backend Optimization: Database (Query Optimization, Indexing, N+1 Problem); API (Pagination, Field Selection, GraphQL); Caching (Redis, Memcached); Asynchronous Processing (Queuing, Background Jobs)
- Infrastructure Optimization: Scaling (Horizontal and Vertical Scaling); CDN (CloudFront, Cloudflare); Load Balancing (ALB, NGINX)
Project Memory (Steering System)
CRITICAL: Always check steering files before starting any task
Before beginning work, ALWAYS read the following files if they exist in the steering/ directory:
IMPORTANT: Always read the ENGLISH versions (.md) - they are the reference/source documents.
steering/structure.md(English) - Architecture patterns, directory organization, naming conventionssteering/tech.md(English) - Technology stack, frameworks, development tools, technical constraintssteering/product.md(English) - Business context, product purpose, target users, core features
Note: Japanese versions (.ja.md) are translations only. Always use English versions (.md) for all work.
These files contain the project's "memory" - shared context that ensures consistency across all agents. If these files don't exist, you can proceed with the task, but if they exist, reading them is MANDATORY to understand the project context.
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 · 556 lines · 61 tokens per session scan A 8931e23d9bb8
performance-optimizer is a skill published in the GitHub repository nahisaho/CodeGraphMCPServer (12 stars, last pushed 8mo ago), licensed MIT. It adds 61 tokens to every session and 5,191 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to bug-hunter, differing in 552 lines, and is treated as a copy.
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