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 endorphin-ai/claude-code-teams --skill qa-frontend-meangit clone --depth 1 https://github.com/endorphin-ai/claude-code-teamsWrote 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/endorphin-ai/claude-code-teams/qa-frontend-mean)<a href="https://agentmods.dev/skills/endorphin-ai/claude-code-teams/qa-frontend-mean"><img src="https://agentmods.dev/badge/skills/endorphin-ai/claude-code-teams/qa-frontend-mean/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/endorphin-ai/claude-code-teams/qa-frontend-mean"><img src="https://agentmods.dev/badge/skills/endorphin-ai/claude-code-teams/qa-frontend-mean.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 | $0.02079 |
| Opus 5 | $0.00024 | $0.01040 |
| Sonnet 5 | $0.00010 | $0.00416 |
| Haiku 4.5 | $0.00005 | $0.00208 |
Grade A, and why
qa-frontend-mean 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 8d 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
What ships with it
6 files 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.
- 8d ago First seen · 243 lines · 48 tokens per session scan A 56169c2275de
qa-frontend-mean is a skill published in the GitHub repository endorphin-ai/claude-code-teams (3 stars, last pushed 6mo ago), with no licence file. It adds 48 tokens to every session and 2,079 once invoked, about $0.0002 per session on Opus 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.
Other skills, from other repositories
web-frontend-tester
Run frontend functional, accessibility, visual, and performance test planning with structured reports.
offensive-fuzzing
Practical offensive fuzzing methodology covering target identification, fuzzer selection (AFL++, libFuzzer, Honggfuzz, Boofuzz, syzkaller), harness writing, corpus curation, mutation strategies, coverage measurement, and crash triage. Use when setting up or running fuzz campaigns against any target: file parsers…
live-preview
Mid-build visual verification loop. Takes screenshots of components during construction, not just after. Catches visual regressions and invisible features before they compound. Requires Playwright or similar screenshot tool.
offensive-race-condition
Race condition (TOCTOU) testing checklist: identifying timing windows, Burp Suite Turbo Intruder, Last-Byte sync technique, rate limit bypass, double-spend attacks, and concurrent request exploitation. Use for web app race condition testing or bug bounty time-of-check-to-time-of-use bugs.
wcag
Expert WCAG (Web Content Accessibility Guidelines) advisor covering WCAG 2.0, 2.1, and 2.2 — the W3C international accessibility standards. Use this skill whenever a user asks about WCAG success criteria, conformance levels (A/AA/AAA), accessibility audits, POUR principles, accessibility statements, ARIA patterns…
render-evidence
Capture the before/after rendered PNGs a UI-affecting PR in this repository needs as visual evidence, including bringing an Android SDK up in a fresh sandbox. Use when a change touches a Compose @Preview, a catalog, the VS Code webview, an overlay, a theme, an icon or a fixture, and the PR body needs real pixels.