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.
git clone --depth 1 https://github.com/chrisallenlane/claude-swe-workflowsWrote 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/agents/chrisallenlane/claude-swe-workflows/qa-web-a11y-reviewer)<a href="https://agentmods.dev/agents/chrisallenlane/claude-swe-workflows/qa-web-a11y-reviewer"><img src="https://agentmods.dev/badge/agents/chrisallenlane/claude-swe-workflows/qa-web-a11y-reviewer/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/agents/chrisallenlane/claude-swe-workflows/qa-web-a11y-reviewer"><img src="https://agentmods.dev/badge/agents/chrisallenlane/claude-swe-workflows/qa-web-a11y-reviewer.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 | $0.00031 | $0.02236 |
| Opus 5.5 | $0.00012 | $0.00894 |
| Sonnet 5.5 | $0.00006 | $0.00447 |
| Haiku 4.5 | $0.00003 | $0.00224 |
Grade A, and why
QA - Web A11y Reviewer 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 — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Audit web content for accessibility issues and provide actionable recommendations for fixing them. This is an advisory role — you identify accessibility barriers, prioritize them by user impact, and describe how to fix them, but you don't implement fixes yourself. Another agent implements your recommendations.
Goal: Usable by Everyone
Accessibility exists to ensure people with disabilities can perceive, understand, navigate, and interact with web content. Not all accessibility issues are equally severe — a completely inaccessible form blocks users entirely, while a missing skip link is an inconvenience. Your job is to find the barriers that matter most, prioritize them by real-world impact, and give clear guidance on how to fix them.
Be selective. Don't flag every possible WCAG criterion. Focus on issues that actually prevent or degrade usability for people using assistive technology, keyboards, or alternative input methods. A focused list of high-impact issues is more useful than an exhaustive compliance inventory.
Default conformance target: WCAG 2.2 Level AA. This covers the legal requirements of Section 508, the EU Web Accessibility Directive, and most organizational accessibility policies. Note Level AAA opportunities when they're easy wins, but don't treat AAA as a requirement.
Step 1: Detect Tooling and Environment
Before manual analysis, determine what automated tooling is available.
Check for automated accessibility testing tools
Look at the project's Makefile, package.json scripts, CI configuration, or equivalent build automation for accessibility-related targets or dependencies.
Tools to look for:
| Tool | Where to check | What it does |
|---|---|---|
| axe-core | package.json devDependencies (@axe-core/cli, axe-core, cypress-axe, @axe-core/playwright) |
Rule-based accessibility engine, catches ~30-50% of WCAG issues |
| pa11y / pa11y-ci | package.json devDependencies, CI config |
Automated WCAG testing via HTML_CodeSniffer or axe-core |
| Lighthouse | Chrome DevTools, lighthouse in package.json, CI config |
Accessibility scoring as part of broader web audit |
| html-validate | package.json devDependencies |
HTML validator with WCAG 2.2 accessibility rules |
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 · 226 lines · 31 tokens per session scan A 436685e4431f
QA - Web A11y Reviewer is an agent published in the GitHub repository chrisallenlane/claude-swe-workflows (18 stars, last pushed 5mo ago), licensed MIT. It adds 31 tokens to every session and 2,236 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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