Borrowing it
Nothing to install: this file belongs to hamzaMissewi/agent-skills. 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/hamzaMissewi/agent-skills/main/.claude/commands/webperf.mdgit clone --depth 1 https://github.com/hamzaMissewi/agent-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/commands/hamzamissewi/agent-skills/webperf)<a href="https://agentmods.dev/commands/hamzamissewi/agent-skills/webperf"><img src="https://agentmods.dev/badge/commands/hamzamissewi/agent-skills/webperf/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/commands/hamzamissewi/agent-skills/webperf"><img src="https://agentmods.dev/badge/commands/hamzamissewi/agent-skills/webperf.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 | $0.00013 | $0.00448 |
| Opus 5 | $0.00006 | $0.00224 |
| Sonnet 5 | $0.00003 | $0.00090 |
| Haiku 4.5 | $0.00001 | $0.00045 |
Grade A, and why
webperf 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 9d 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
100% identical to webperf — 0 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.
What it actually says
/webperf targets web applications specifically. Do not use it for utility libraries, CLIs, or server-only code with no browser-facing output.
Determine the mode
Deep mode — activate when any of these is available:
- A Lighthouse JSON report file (e.g.
npx lighthouse <url> --output json --output-path ./report.json, ornpx -p chrome-devtools-mcp chrome-devtools lighthouse_audit --output-format=jsonfrom the Chrome DevTools MCP CLI) - A PageSpeed Insights JSON response (includes Lighthouse + CrUX)
- A CrUX API response (requires
CRUX_API_KEYorGOOGLE_API_KEY) - A DevTools performance trace
- A live URL plus the
chrome-devtoolsMCP server configured in the harness (the agent can capture metrics directly vialighthouse_auditandperformance_*tools) - The Chrome DevTools MCP CLI invoked locally (via
npx -p chrome-devtools-mcp chrome-devtools <tool>or afternpm i -g chrome-devtools-mcp) — the user runs commands likechrome-devtools lighthouse_audit --output-format=jsonand passes the JSON output to the agent
Quick mode — default when none of the above are available. The agent scans source code for structural anti-patterns and labels every finding as potential impact.
Run the audit
Spawn the web-performance-auditor subagent. Pass it explicitly:
- The files, components, or diff under review
- Any artifact paths (Lighthouse JSON, PSI JSON, CrUX response, trace) or pasted JSON content
- The target URL or page name when known
- A note on which mode you expect (Quick or Deep), so the agent surfaces missing inputs if Deep was intended
The subagent returns a scorecard (only populated with sourced values), a ranked list of findings, positive observations, and proactive recommendations.
Output
Return the full audit report to the user. No synthesis or merge step is needed — this is a single-persona command.
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.
- 9d ago First seen · 33 lines · 13 tokens per session scan A 74c0c1335f13
webperf is a command published in the GitHub repository hamzaMissewi/agent-skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 13 tokens to every session and 448 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to webperf, differing in 0 lines, and is treated as a copy.
Other commands, from other repositories
ui-flow-review
Review menus, HUD, navigation, and player flow from a UX perspective.
responsive-design-specialist
Use when a layout breaks between sizes. Arbitrary breakpoints, type that does not scale, images that blow out the grid, or a desktop design retrofitted onto mobile.
design-form
Design a form with the fewest fields that works, clear labels, and errors that help.
frontend-3d
You are an expert in 3D web development using Three.js, React Three Fiber, WebGL, and WebGPU. You create immersive 3D experiences for the web.
frontend-design
Read and follow the instructions in agents/frontend-design/design-all.md. Also read all referenced files in agents/frontend-design/reference/ as needed for the task.
get-component-source
The full TSX source of a component (append " demo" for its usage example).