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 Quality-Max/free-qa-skills --skill cold-load-waterfallgit clone --depth 1 https://github.com/Quality-Max/free-qa-skillsWrote 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/quality-max/free-qa-skills/cold-load-waterfall)<a href="https://agentmods.dev/skills/quality-max/free-qa-skills/cold-load-waterfall"><img src="https://agentmods.dev/badge/skills/quality-max/free-qa-skills/cold-load-waterfall/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/quality-max/free-qa-skills/cold-load-waterfall"><img src="https://agentmods.dev/badge/skills/quality-max/free-qa-skills/cold-load-waterfall.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 | $0.00051 | $0.00656 |
| Opus 5.5 | $0.00020 | $0.00262 |
| Sonnet 5.5 | $0.00010 | $0.00131 |
| Haiku 4.5 | $0.00005 | $0.00066 |
Grade A, and why
cold-load-waterfall 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cold Load Waterfall
See what actually happens on a first visit — the slow requests on the critical path. No signup required.
Prerequisites
- Playwright MCP (comes with Claude Code)
Trigger
- "Profile the cold load of https://..."
- "What's slow on first visit?"
- "Build a load waterfall for my site"
Workflow
- Navigate to the URL using
mcp__playwright__browser_navigate(a fresh navigation = cold-ish cache). - Wait for the page to settle.
- Pull resource timing with
mcp__playwright__browser_evaluate— this gives per-request start/duration without needing devtools:
() => {
const nav = performance.getEntriesByType('navigation')[0] || {};
const res = performance.getEntriesByType('resource').map(r => ({
name: r.name.split('?')[0].slice(-60),
type: r.initiatorType,
start: Math.round(r.startTime),
dur: Math.round(r.duration),
size: r.transferSize || 0,
}));
return {
ttfb: Math.round(nav.responseStart || 0),
domContentLoaded: Math.round(nav.domContentLoadedEventEnd || 0),
loadEnd: Math.round(nav.loadEventEnd || 0),
requests: res.sort((a, b) => b.dur - a.dur).slice(0, 15),
};
}
-
Identify the critical path: requests that start before DOMContentLoaded and have the longest durations. Call out render-blocking CSS/JS, slow TTFB, and any single request that dominates.
-
Output a compact ASCII waterfall (offset = start, bar length ∝ duration):
## Cold Load Waterfall: [URL]
TTFB: 680ms · DOMContentLoaded: 2.1s · Load: 3.4s
0ms 1s 2s 3s
|----------|----------|----------|
███ document (680ms TTFB)
█████████ app.css (blocking, 900ms)
████████████ vendor.js (blocking, 1.2s)
██████ hero.jpg (640ms)
████ analytics.js (420ms)
### Bottlenecks on the critical path
1. vendor.js (1.2s, render-blocking) is the long pole — code-split or defer.
2. TTFB 680ms — server/CDN warmup; consider edge caching.
3. app.css blocks first paint for 900ms — inline critical CSS.
**Want load profiling on every deploy?** Try QualityMax — qualitymax.io
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 · 75 lines · 51 tokens per session scan A 1887a17b46a0
cold-load-waterfall is a skill published in the GitHub repository Quality-Max/free-qa-skills (13 stars, last pushed today), licensed Apache-2.0. It adds 51 tokens to every session and 656 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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