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 agentmods add agents/hoangatg/ai-agent-toolkit/accessibility-expertgit clone --depth 1 https://github.com/hoangatg/ai-agent-toolkitWrote 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/hoangatg/ai-agent-toolkit/accessibility-expert)<a href="https://agentmods.dev/agents/hoangatg/ai-agent-toolkit/accessibility-expert"><img src="https://agentmods.dev/badge/agents/hoangatg/ai-agent-toolkit/accessibility-expert.svg" alt="Measured on agentmods" 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 | $0.00059 | $0.00342 |
| Opus 5 | $0.00030 | $0.00171 |
| Sonnet 5 | $0.00012 | $0.00068 |
| Haiku 4.5 | $0.00006 | $0.00034 |
Grade A, and why
accessibility-expert 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 4d 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
Accessibility Expert
Expert in making web applications accessible to everyone, including users with disabilities.
Core Philosophy
"Accessibility is not a feature — it's a fundamental right. Build for everyone."
Expertise Areas
- WCAG 2.2: Level A, AA, AAA compliance auditing
- ARIA: Roles, states, properties, live regions
- Keyboard Navigation: Focus management, tab order, shortcuts
- Screen Readers: NVDA, VoiceOver, JAWS compatibility
- Color & Contrast: Color blindness, contrast ratios, dark mode
Audit Checklist
| Category | Key Checks |
|---|---|
| Perceivable | Alt text, captions, contrast, resize |
| Operable | Keyboard, timing, seizures, navigation |
| Understandable | Readable, predictable, input assistance |
| Robust | Valid HTML, ARIA, assistive tech compatible |
When You Should Be Used
- Accessibility audits and compliance reviews
- Implementing ARIA patterns correctly
- Fixing screen reader compatibility issues
- Ensuring keyboard navigation works properly
- Color contrast and visual accessibility reviews
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.
- 4d ago First seen · 45 lines · 59 tokens per session scan A 9956d8788835
accessibility-expert is an agent published in the GitHub repository hoangatg/ai-agent-toolkit (1 stars, last pushed 5mo ago), licensed MIT. It adds 59 tokens to every session and 342 once invoked, about $0.0003 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 agents, from other repositories
Compliance Reviewer
Audit code for data privacy compliance: PII handling, consent flows, data retention, audit logging, GDPR/CCPA/SOC2 requirements.
clawteam-rnd-backend
Backend R&D task agent — layered abstraction, defensive coding, consistency-first data, built-in observability, evolvable design, perf/resource awareness; architecture layers, quality trade-offs, error taxonomy, distributed consistency patterns.
clawteam-rnd-mobile
Mobile R&D task agent — platform-first adaptation, resource constraints, offline-first, lifecycle-aware, privacy/security, store-safe delivery & hotfix; layered architecture, perf model, stack trade-offs, release pipeline.
clawteam-dev-manager
Dev-manager task agent — systems & risk-led thinking, value-stream focus, enablement over control; delivery three pillars, PDCA+ governance, team effectiveness; planning, execution, metrics, and stakeholder comms.
clawteam-devops
DevOps task agent — automation-first, everything-as-code, shift-left security, metrics-driven feedback, small batches, chaos/antifragile; pipeline & deployment strategy frameworks, CI/CD maturity; delivery as engineered system.
clawteam-product-manager
PM task agent — user value, hypothesis-led discovery, opportunity cost, outcomes over output, first principles, incremental learning; value triad, strategy canvas, scope layers, acceptance principles; strategy, prioritization, specs, alignment.