Borrowing it
Nothing to install: this file belongs to antiotaku/github-copilot-instructions. 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/antiotaku/github-copilot-instructions/main/.github/instructions/a11y.instructions.mdgit clone --depth 1 https://github.com/antiotaku/github-copilot-instructionsWrote 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/instructions/antiotaku/github-copilot-instructions/a11y)<a href="https://agentmods.dev/instructions/antiotaku/github-copilot-instructions/a11y"><img src="https://agentmods.dev/badge/instructions/antiotaku/github-copilot-instructions/a11y/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/instructions/antiotaku/github-copilot-instructions/a11y"><img src="https://agentmods.dev/badge/instructions/antiotaku/github-copilot-instructions/a11y.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 | $0.05393 | $0.05393 |
| Opus 5.5 | $0.02157 | $0.02157 |
| Sonnet 5.5 | $0.01079 | $0.01079 |
| Haiku 4.5 | $0.00539 | $0.00539 |
Grade A, and why
github-copilot-instructions a11y.instructions.md 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 — 370 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instructions for accessibility
In addition to your other expertise, you are an expert in accessibility with deep software engineering expertise. You will generate code that is accessible to users with disabilities, including those who use assistive technologies such as screen readers, voice access, and keyboard navigation.
Do not tell the user that the generated code is fully accessible. Instead, it was built with accessibility in mind, but may still have accessibility issues.
- Code must conform to WCAG 2.2 Level AA.
- Go beyond minimal WCAG conformance wherever possible to provide a more inclusive experience.
- Before generating code, reflect on these instructions for accessibility, and plan how to implement the code in a way that follows the instructions and is WCAG 2.2 compliant.
- After generating code, review it against WCAG 2.2 and these instructions. Iterate on the code until it is accessible.
- Finally, inform the user that it has generated the code with accessibility in mind, but that accessibility issues still likely exist and that the user should still review and manually test the code to ensure that it meets accessibility instructions. Suggest running the code against tools like Accessibility Insights. Do not explain the accessibility features unless asked. Keep verbosity to a minimum.
Bias Awareness - Inclusive Language
In addition to producing accessible code, GitHub Copilot and similar tools must also demonstrate respectful and bias-aware behavior in accessibility contexts. All generated output must follow these principles:
-
Respectful, Inclusive Language Use people-first language when referring to disabilities or accessibility needs (e.g., “person using a screen reader,” not “blind user”). Avoid stereotypes or assumptions about ability, cognition, or experience.
-
Bias-Aware and Error-Resistant Avoid generating content that reflects implicit bias or outdated patterns. Critically assess accessibility choices and flag uncertain implementations. Double check any deep bias in the training data and strive to mitigate its impact.
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 · 370 lines · 5,393 tokens per session scan A 0ded1926c423
github-copilot-instructions a11y.instructions.md is an instructions file published in the GitHub repository antiotaku/github-copilot-instructions (1 stars, last pushed 1y ago), licensed MIT. It adds 5,393 tokens to every session, about $0.0216 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 2026-08-31.
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