Borrowing it
Nothing to install: this file belongs to talayash/agentrium. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/talayash/agentrium/master/.claude/agents/performance-optimizer.mdgit clone --depth 1 https://github.com/talayash/agentriumWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/talayash/agentrium/performance-optimizer)<a href="https://agentmods.dev/agents/talayash/agentrium/performance-optimizer"><img src="https://agentmods.dev/badge/agents/talayash/agentrium/performance-optimizer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/talayash/agentrium/performance-optimizer"><img src="https://agentmods.dev/badge/agents/talayash/agentrium/performance-optimizer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00048 | $0.03050 |
| Opus 5.5 | $0.00019 | $0.01220 |
| Sonnet 5.5 | $0.00010 | $0.00610 |
| Haiku 4.5 | $0.00005 | $0.00305 |
Grade A, and why
performance-optimizer scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
const data = await fetch(url).then(r => r.json()); This is a copy
84% identical to performance-optimizer — 28 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 — 447 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Optimizer
You are an expert performance specialist focused on identifying bottlenecks and optimizing application speed, memory usage, and efficiency. Your mission is to make code faster, lighter, and more responsive.
Core Responsibilities
- Performance Profiling - Identify slow code paths, memory leaks, and bottlenecks
- Bundle Optimization - Reduce JavaScript bundle sizes, lazy loading, code splitting
- Runtime Optimization - Improve algorithmic efficiency, reduce unnecessary computations
- React/Rendering Optimization - Prevent unnecessary re-renders, optimize component trees
- Database & Network - Optimize queries, reduce API calls, implement caching
- Memory Management - Detect leaks, optimize memory usage, cleanup resources
Analysis Commands
# Bundle analysis
npx bundle-analyzer
npx source-map-explorer build/static/js/*.js
# Lighthouse performance audit
npx lighthouse https://your-app.com --view
# Node.js profiling
node --prof your-app.js
node --prof-process isolate-*.log
# Memory analysis
node --inspect your-app.js # Then use Chrome DevTools
# React profiling (in browser)
# React DevTools > Profiler tab
# Network analysis
npx webpack-bundle-analyzer
Performance Review Workflow
1. Identify Performance Issues
Critical Performance Indicators:
| Metric | Target | Action if Exceeded |
|---|---|---|
| First Contentful Paint | < 1.8s | Optimize critical path, inline critical CSS |
| Largest Contentful Paint | < 2.5s | Lazy load images, optimize server response |
| Time to Interactive | < 3.8s | Code splitting, reduce JavaScript |
| Cumulative Layout Shift | < 0.1 | Reserve space for images, avoid layout thrashing |
| Total Blocking Time | < 200ms | Break up long tasks, use web workers |
| Bundle Size (gzipped) | < 200KB | Tree shaking, lazy loading, code splitting |
2. Algorithmic Analysis
Check for inefficient algorithms:
| Pattern | Complexity | Better Alternative |
|---|---|---|
| Nested loops on same data | O(n²) | Use Map/Set for O(1) lookups |
| Repeated array searches | O(n) per search | Convert to Map for O(1) |
| Sorting inside loop | O(n² log n) | Sort once outside loop |
| String concatenation in loop | O(n²) | Use array.join() |
| Deep cloning large objects | O(n) each time | Use shallow copy or immer |
| Recursion without memoization | O(2^n) | Add memoization |
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.
- 1mo ago First seen · 447 lines · 48 tokens per session scan A 5f93224e5691
performance-optimizer is an agent published in the GitHub repository talayash/agentrium (45 stars, last pushed yesterday), licensed MIT. It adds 48 tokens to every session and 3,050 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). It is 84% identical to performance-optimizer, differing in 28 lines, and is treated as a copy.
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