Borrowing it
Nothing to install: this file belongs to Piyush8296/claude-workspace. 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/Piyush8296/claude-workspace/main/.claude/skills/performance-optimization/SKILL.mdgit clone --depth 1 https://github.com/Piyush8296/claude-workspaceWrote 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/skills/piyush8296/claude-workspace/performance-optimization)<a href="https://agentmods.dev/skills/piyush8296/claude-workspace/performance-optimization"><img src="https://agentmods.dev/badge/skills/piyush8296/claude-workspace/performance-optimization/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/skills/piyush8296/claude-workspace/performance-optimization"><img src="https://agentmods.dev/badge/skills/piyush8296/claude-workspace/performance-optimization.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 | $0.00040 | $0.01651 |
| Opus 5.5 | $0.00016 | $0.00660 |
| Sonnet 5.5 | $0.00008 | $0.00330 |
| Haiku 4.5 | $0.00004 | $0.00165 |
Grade A, and why
performance-optimization 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 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.
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 — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Optimization
Core Web Vitals Targets
| Metric | Good | Needs Work | Poor |
|---|---|---|---|
| LCP (Largest Contentful Paint) | ≤ 2.5s | ≤ 4.0s | > 4.0s |
| INP (Interaction to Next Paint) | ≤ 200ms | ≤ 500ms | > 500ms |
| CLS (Cumulative Layout Shift) | ≤ 0.1 | ≤ 0.25 | > 0.25 |
Bundle Optimization
Code Splitting
import { lazy, Suspense } from 'react';
// Route-level splitting (mandatory)
const Dashboard = lazy(() => import('./pages/Dashboard'));
const Settings = lazy(() => import('./pages/Settings'));
// Component-level splitting (for heavy components)
const MarkdownEditor = lazy(() => import('./components/MarkdownEditor'));
const ChartWidget = lazy(() => import('./components/ChartWidget'));
// Always wrap with Suspense + meaningful fallback
<Suspense fallback={<DashboardSkeleton />}>
<Dashboard />
</Suspense>
Tree-Shaking
// BAD: imports entire library
import _ from 'lodash';
_.debounce(fn, 300);
// GOOD: imports only what's needed
import debounce from 'lodash/debounce';
debounce(fn, 300);
// BEST: use native or lightweight alternative
function debounce<T extends (...args: unknown[]) => void>(fn: T, ms: number) {
let timer: ReturnType<typeof setTimeout>;
return (...args: Parameters<T>) => {
clearTimeout(timer);
timer = setTimeout(() => fn(...args), ms);
};
}
Import Analysis
# Analyze bundle composition
npx vite-bundle-visualizer # Vite
npx @next/bundle-analyzer # Next.js
# Find heavy dependencies
du -sh node_modules/* | sort -rh | head -20
React Rendering Optimization
When to Memoize
// MEMOIZE: Expensive computation
const sortedItems = useMemo(
() => items.sort((a, b) => b.date - a.date),
[items]
);
// MEMOIZE: Referential stability for child components
const handleSubmit = useCallback(
(data: FormData) => {
submitMutation.mutate(data);
},
[submitMutation.mutate]
);
// DON'T MEMOIZE: Simple computation
// const fullName = useMemo(() => `${first} ${last}`, [first, last]);
const fullName = `${first} ${last}`; // Just compute it
// DON'T MEMOIZE: Primitive props
// const title = useMemo(() => 'Hello', []);
const title = 'Hello'; // Primitives are already stable
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 · 254 lines · 40 tokens per session scan A ad57326857f0
performance-optimization is a skill published in the GitHub repository Piyush8296/claude-workspace (2 stars, last pushed 6mo ago), licensed MIT. It adds 40 tokens to every session and 1,651 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.
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