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 mtarcure/claude-vibe-squad --skill wcag-conformance-auditgit clone --depth 1 https://github.com/mtarcure/claude-vibe-squadWrote 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/mtarcure/claude-vibe-squad/wcag-conformance-audit)<a href="https://agentmods.dev/skills/mtarcure/claude-vibe-squad/wcag-conformance-audit"><img src="https://agentmods.dev/badge/skills/mtarcure/claude-vibe-squad/wcag-conformance-audit/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/mtarcure/claude-vibe-squad/wcag-conformance-audit"><img src="https://agentmods.dev/badge/skills/mtarcure/claude-vibe-squad/wcag-conformance-audit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00056 | $0.00240 |
| Opus 5.5 | $0.00022 | $0.00096 |
| Sonnet 5.5 | $0.00011 | $0.00048 |
| Haiku 4.5 | $0.00006 | $0.00024 |
Grade A, and why
wcag-conformance-audit 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 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.
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.
What it actually says
WCAG Conformance Audit
Audit a UI or media asset against a WCAG target with per-criterion evidence — not a screenshot glance.
Steps
- Set the conformance target (WCAG 2.2 A / AA / AAA) and platform.
- Audit beyond the visible: semantic/accessibility tree, keyboard/focus order and traps, contrast, zoom/reflow, motion, input alternatives, screen-reader behavior.
- Cite the specific success criterion for every finding; rate severity.
- Specify an engineer-actionable remediation per finding.
- Return PASS/HOLD; document automated-tool limitations rather than trusting them.
Acceptance
- Every finding cites a WCAG success criterion.
- Keyboard and screen-reader behavior are covered; a screenshot/automated pass alone is never PASS.
- Remediations are specific and actionable.
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 · 22 lines · 56 tokens per session scan A 175f5c5a2c41
wcag-conformance-audit is a skill published in the GitHub repository mtarcure/claude-vibe-squad (211 stars, last pushed yesterday), licensed MIT. It adds 56 tokens to every session and 240 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 2026-08-30.
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