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 tan-yong-sheng/ai-vision-mcp --skill wcag-compliancegit clone --depth 1 https://github.com/tan-yong-sheng/ai-vision-mcpWrote 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/tan-yong-sheng/ai-vision-mcp/wcag-compliance)<a href="https://agentmods.dev/skills/tan-yong-sheng/ai-vision-mcp/wcag-compliance"><img src="https://agentmods.dev/badge/skills/tan-yong-sheng/ai-vision-mcp/wcag-compliance/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/tan-yong-sheng/ai-vision-mcp/wcag-compliance"><img src="https://agentmods.dev/badge/skills/tan-yong-sheng/ai-vision-mcp/wcag-compliance.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 | $0.00036 | $0.01488 |
| Opus 5.5 | $0.00014 | $0.00595 |
| Sonnet 5.5 | $0.00007 | $0.00298 |
| Haiku 4.5 | $0.00004 | $0.00149 |
Grade A, and why
wcag-compliance 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 — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WCAG Compliance
Deep accessibility compliance guidance for WCAG 2.1 (compliance-focused) and WCAG 3.0 (outcome-focused) standards.
When to Use
Use this skill when:
- Auditing for WCAG 2.1 or WCAG 3.0 compliance
- Mapping findings to specific WCAG criteria
- Providing remediation guidance with code examples
- Testing accessibility fixes
- Explaining user impact and accommodation needs
Reference Materials
This skill includes comprehensive reference documentation:
- wcag-2.2-complete-criteria.md — All 78 WCAG 2.2 success criteria organized by level (A, AA, AAA) with common issues and remediation guidance
- wcag-3.0-outcomes-framework.md — Outcome-focused accessibility framework, paradigm shift from WCAG 2.1, audit workflow, and remediation patterns
- aria-patterns-reference.md — 13 essential ARIA patterns with code examples, keyboard support, and screen reader behavior
- A11Y-PATTERNS.md — Copy-paste-ready accessibility code patterns (modal focus trap, skip link, error handling, form labels, dragging movements, tabs, live regions, screen reader commands)
WCAG 2.1 vs WCAG 3.0: Paradigm Shift
WCAG 2.1 (Compliance-Focused): Binary pass/fail against specific technical criteria. Levels: A (minimum), AA (standard), AAA (enhanced).
WCAG 3.0 (Outcome-Focused): Outcome-centered goals focusing on user ability. Four dimensions: Perceivable, Operable, Understandable, Robust.
See → wcag-3.0-outcomes-framework.md for detailed comparison, paradigm differences, and outcome-focused audit workflow.
Quick Start: 3-Phase Accessibility Workflow
Phase 1: Scan & Analyze
- Run automated tools (axe, WAVE, Lighthouse, Pa11y)
- Conduct keyboard navigation and screen reader testing
- Map findings to WCAG criteria
- Prioritize: Critical (blocks) > High > Medium > Low
What ships with it
4 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.
- 1mo ago First seen · 132 lines · 36 tokens per session scan A 21119661542e
wcag-compliance is a skill published in the GitHub repository tan-yong-sheng/ai-vision-mcp (80 stars, last pushed 6mo ago), licensed MIT. It adds 36 tokens to every session and 1,488 once invoked, about $0.0001 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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