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 beita6969/ScienceClaw --skill medical-qagit clone --depth 1 https://github.com/beita6969/ScienceClawWrote 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/beita6969/scienceclaw/medical-qa)<a href="https://agentmods.dev/skills/beita6969/scienceclaw/medical-qa"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/medical-qa/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/beita6969/scienceclaw/medical-qa"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/medical-qa.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00015 | $0.00358 |
| Opus 5 | $0.00008 | $0.00179 |
| Sonnet 5 | $0.00003 | $0.00072 |
| Haiku 4.5 | $0.00002 | $0.00036 |
Grade A, and why
medical-qa 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 9d 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
Medical Question Answering
Purpose
Answer medical and biomedical questions with evidence-based precision using structured datasets and clinical knowledge bases.
Key Datasets
- MedQuAD (abachaa/MedQuAD): 47,457 QA pairs from 12 NIH sources (NCI, GARD, GHR, MedlinePlus, NIDDK, NHLBI, NICHD, NIA, NIAMS, NINDS, NIDA, GARD)
- PubMedQA (qiaojin/PubMedQA): Yes/No/Maybe reasoning from PubMed abstracts
Protocol
- Parse the question — Identify medical entities (diseases, drugs, genes, symptoms)
- Source identification — Match question type to appropriate NIH source
- Evidence retrieval — Search PubMed, clinical guidelines, drug databases
- Answer synthesis — Provide answer with confidence level and citations
- Verification — Cross-reference with at least 2 independent sources
Question Types
- Disease/condition: Etiology, diagnosis, prognosis, treatment
- Drug/treatment: Mechanism, dosage, side effects, interactions
- Genetic: Gene function, variants, inheritance patterns
- Prevention: Risk factors, screening, lifestyle modifications
Rules
- Always cite primary sources (PMID, DOI, or guideline reference)
- Distinguish between established evidence and emerging research
- Flag when evidence is limited or conflicting
- Never provide personalized medical advice
- Include confidence level: HIGH (multiple RCTs), MODERATE (observational), LOW (case reports)
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.
- 9d ago First seen · 34 lines · 15 tokens per session scan A 35ce8cf610f5
medical-qa is a skill published in the GitHub repository beita6969/ScienceClaw (898 stars, last pushed 3mo ago), licensed MIT. It adds 15 tokens to every session and 358 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 2026-09-03.
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