Borrowing it
Nothing to install: this file belongs to 2023Anita/clinical-ai-agent-skills. 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/2023Anita/clinical-ai-agent-skills/main/.github/copilot-instructions.mdgit clone --depth 1 https://github.com/2023Anita/clinical-ai-agent-skillsWrote 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/2023anita/clinical-ai-agent-skills/copilot-instructions)<a href="https://agentmods.dev/instructions/2023anita/clinical-ai-agent-skills/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/2023anita/clinical-ai-agent-skills/copilot-instructions/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/2023anita/clinical-ai-agent-skills/copilot-instructions"><img src="https://agentmods.dev/badge/instructions/2023anita/clinical-ai-agent-skills/copilot-instructions.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 | $0.00156 | $0.00156 |
| Opus 5 | $0.00078 | $0.00078 |
| Sonnet 5 | $0.00031 | $0.00031 |
| Haiku 4.5 | $0.00016 | $0.00016 |
Grade A, and why
clinical-ai-agent-skills copilot-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 11d 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
Clinical AI Agent Rules for GitHub Copilot
Follow these repository rules when generating code, documentation, examples, or comments.
- Use plain language suitable for clinicians and medical AI beginners.
- Do not invent citations, medical guidelines, PubMed IDs, trial results, or clinical recommendations.
- Do not create patient-specific diagnosis, treatment, triage, dosing, or decision-support content.
- Keep medical outputs clearly framed as research, education, documentation, or engineering assistance.
- Avoid private patient data, credentials, secrets, or identifiable medical information.
- Prefer small, readable changes over speculative abstractions.
- Do not add complex frameworks unless the task requires them.
- When writing examples, use synthetic data only.
- When writing safety notes, be clear but not alarmist.
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.
- 11d ago First seen · 15 lines · 156 tokens per session scan A fa41b4893804
clinical-ai-agent-skills copilot-instructions.md is an instructions file published in the GitHub repository 2023Anita/clinical-ai-agent-skills (2 stars, last pushed 3mo ago), licensed MIT. It adds 156 tokens to every session, about $0.0008 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.
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