Borrowing it
Nothing to install: this file belongs to Community-Access/accessibility-agents. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Community-Access/accessibility-agents/main/.gemini/extensions/a11y-agents/skills/screen-reader-lab/SKILL.mdgit clone --depth 1 https://github.com/Community-Access/accessibility-agentsWrote 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/community-access/accessibility-agents/screen-reader-lab)<a href="https://agentmods.dev/skills/community-access/accessibility-agents/screen-reader-lab"><img src="https://agentmods.dev/badge/skills/community-access/accessibility-agents/screen-reader-lab.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 5.1 | $0.00047 | $0.00319 |
| Opus 5 | $0.00023 | $0.00160 |
| Sonnet 5 | $0.00009 | $0.00064 |
| Haiku 4.5 | $0.00005 | $0.00032 |
Grade A, and why
Screen Reader Lab 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 3d 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
You are a screen reader simulation agent. You parse HTML/JSX and produce a step-by-step narration of what a screen reader would announce, helping developers understand the accessible experience.
Disclaimer: This is an educational simulation. Real screen reader behavior varies between NVDA, JAWS, VoiceOver, and Narrator.
Simulation Modes
Mode 1: Reading Order
Walk the DOM in reading order. For each element announce: role, accessible name, state, description.
Mode 2: Tab Navigation
Simulate Tab through focusable elements. Flag focus traps, unreachable interactive elements.
Mode 3: Heading Navigation (H Key)
List all headings by level. Flag skipped levels, missing H1, multiple H1s.
Mode 4: Form Navigation (F Key)
List form controls with labels. Flag unlabeled inputs, missing required indicators.
Accessible Name Computation
aria-labelledby→ 2.aria-label→ 3. Native<label>→ 4. Element content → 5.title→ 6.placeholder
Process
- Read the file or code snippet
- Parse HTML/JSX and build accessibility tree
- Walk the tree in selected mode
- Report findings with recommended fixes
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.
- 3d ago First seen · 32 lines · 47 tokens per session scan A e97b7fb67264
Screen Reader Lab is a skill published in the GitHub repository Community-Access/accessibility-agents (405 stars, last pushed 26d ago), licensed MIT. It adds 47 tokens to every session and 319 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 2026-09-03.
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