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 skills add san-npm/skills-ws --skill web-performancegit clone --depth 1 https://github.com/san-npm/skills-wsWrote 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/san-npm/skills-ws/web-performance)<a href="https://agentmods.dev/skills/san-npm/skills-ws/web-performance"><img src="https://agentmods.dev/badge/skills/san-npm/skills-ws/web-performance/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/san-npm/skills-ws/web-performance"><img src="https://agentmods.dev/badge/skills/san-npm/skills-ws/web-performance.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 | $0.00064 | $0.03336 |
| Opus 5.5 | $0.00026 | $0.01334 |
| Sonnet 5.5 | $0.00013 | $0.00667 |
| Haiku 4.5 | $0.00006 | $0.00334 |
Grade A, and why
web-performance 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 2mo 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.
curl -so /dev/null -w '%{size_download}' https://example.com How it starts
The opening of the file, as written. The whole thing — 325 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Web Performance
Core Web Vitals
| Metric | Good | Needs Work | Poor | What it measures |
|---|---|---|---|---|
| LCP | ≤2.5s | ≤4.0s | >4.0s | Largest visible content render |
| INP | ≤200ms | ≤500ms | >500ms | Input responsiveness |
| CLS | ≤0.1 | ≤0.25 | >0.25 | Visual stability |
LCP Fixes
- Preload LCP image:
<link rel="preload" as="image" href="/hero.webp"> - Inline critical CSS (eliminate render-blocking)
- Server response <200ms (TTFB): optimize DB queries, use edge caching
- Avoid lazy-loading above-fold images — use
loading="eager"or omit attribute - Use
fetchpriority="high"on LCP element
INP Fixes
- Break long tasks (>50ms) by yielding to the main thread. There is no standalone
yield()in browsers; usescheduler.yield()where available (Chromium 129+ and Firefox 142+; not in Safari as of Jul 2026) with asetTimeout(0)fallback. - Defer non-critical JS:
<script defer>or dynamicimport() - Use
requestIdleCallbackfor analytics/telemetry — but it is unsupported in Safari (use asetTimeoutshim) and always pass atimeoutso the work runs even if the page never goes idle. - Debounce input handlers: 100-150ms for search, immediate for buttons
// Yield to the main thread, with feature detection + fallback.
// scheduler.yield() resumes at high priority (front of queue);
// setTimeout(0) is the universal fallback (resumes after pending tasks).
function yieldToMain() {
if ('scheduler' in window && 'yield' in scheduler) {
return scheduler.yield();
}
return new Promise(r => setTimeout(r, 0));
}
async function processItems(items) {
let lastYield = performance.now();
for (const item of items) {
process(item);
// Yield every ~50ms so input stays responsive.
if (performance.now() - lastYield > 50) {
await yieldToMain();
lastYield = performance.now();
}
}
}
// requestIdleCallback with Safari shim + mandatory timeout.
const ric = window.requestIdleCallback
|| ((cb) => setTimeout(() => cb({ didTimeout: true, timeRemaining: () => 0 }), 1));
ric(() => sendTelemetry(), { timeout: 2000 }); // runs within 2s even if never idle
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 325 lines · 64 tokens per session scan A 1928fa6b1fa4
web-performance is a skill published in the GitHub repository san-npm/skills-ws (4 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 3,336 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-07.
web-performance compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| web-performancesan-npm/skills-ws | Skill | 4 | 1mo ago | MIT | A | 64 | Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |