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 skills add alivirgo/Major-AI-Skills --skill dont-trust-ai-medical-diagnosesgit clone --depth 1 https://github.com/alivirgo/Major-AI-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/skills/alivirgo/major-ai-skills/dont-trust-ai-medical-diagnoses)<a href="https://agentmods.dev/skills/alivirgo/major-ai-skills/dont-trust-ai-medical-diagnoses"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/dont-trust-ai-medical-diagnoses/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/skills/alivirgo/major-ai-skills/dont-trust-ai-medical-diagnoses"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/dont-trust-ai-medical-diagnoses.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 | $0.00028 | $0.01061 |
| Opus 5 | $0.00014 | $0.00531 |
| Sonnet 5 | $0.00006 | $0.00212 |
| Haiku 4.5 | $0.00003 | $0.00106 |
Grade A, and why
dont-trust-ai-medical-diagnoses 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 yesterday.
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 — 104 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Don't Trust AI Medical Diagnoses (Health Literacy Framework) (AI Skill)
Overview
Searching symptoms or pasting medical reports into an AI assistant often triggers extreme responses: either catastrophic worst-case diagnoses (e.g. rare autoimmune conditions or oncology) or false reassurance that causes patients to delay critical in-person care.
The Health Literacy & Doctor-Prep Protocol establishes strict boundaries: never use AI to diagnose illnesses or prescribe dosages, but leverage its strength to translate complex clinical jargon, explain anatomical mechanisms, and generate organized questions for your physician.
The Medical AI Safety Boundary
┌─────────────────────────────────────────────────────────────┐
│ Safe vs. Dangerous Medical AI │
│ │
│ ❌ DANGEROUS USE CASES (Do Not Outsource to AI): │
│ • Diagnosing chest pain, acute abdominal pain, or rashes │
│ • Adjusting prescription medication dosages │
│ • Deciding whether to skip emergency medical care │
│ │
│ ✅ SAFE, HIGH-LEVERAGE USE CASES (Literacy & Prep): │
│ • Translating lab report acronyms (e.g. eGFR, ALT, MCV) │
│ • Understanding standard anatomical terminology │
│ • Generating a prioritized list of questions for your doctor│
└─────────────────────────────────────────────────────────────┘
Master Health Literacy Prompt Templates
Pattern 1: The Lab Report Jargon Translator
Use to demystify complex lab results before your doctor appointment:
Here is a line from my lab report:
"[PASTE SPECIFIC LAB TEST NAME & REFERENCE RANGE]"
Task:
1. Explain what [TEST NAME] measures in plain English using a simple biological analogy.
2. What is the standard purpose of this test in routine checkups?
3. Generate 2 clear, informed questions I can ask my physician during my follow-up appointment.
Do NOT attempt to diagnose my health or tell me if I have a disease.
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.
- yesterday Changed · -9 tokens per session bf4f81dd71b6
- 7d ago First seen · 104 lines · 37 tokens per session scan A 55eaa52757ae
dont-trust-ai-medical-diagnoses is a skill published in the GitHub repository alivirgo/Major-AI-Skills (1 stars, last pushed today), licensed MIT. It adds 28 tokens to every session and 1,061 once invoked, about $0.0001 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 2026-09-05.
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