Medical Research Agent Skills is a library of agent instructions for medical and biomedical research, covering evidence analysis, study protocol design, data analysis, and academic writing. Researchers use it to guide compatible coding agents through common scientific workflows. The catalogue contains many of the library's skills and commands.
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 aipoch/medical-research-skills --skill find-paper-referencesgit clone --depth 1 https://github.com/aipoch/medical-research-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/aipoch/medical-research-skills/find-paper-references)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/find-paper-references"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/find-paper-references/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/aipoch/medical-research-skills/find-paper-references"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/find-paper-references.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 282 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00055 | $0.03113 |
| Opus 5 | $0.00028 | $0.01556 |
| Sonnet 5 | $0.00011 | $0.00623 |
| Haiku 4.5 | $0.00006 | $0.00311 |
Grade A, and why
find-paper-references 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.
How it starts
The opening of the file, as written. The whole thing — 300 lines — stays where its author put it; the contents beside it link to each section on GitHub.
find-paper-references — Academic Paper PubMed Reference Finder
Tools
Scripts are located in the scripts/ subdirectory of this skill:
batch_search.py— Main entry point: accepts all queries at once, parallel search, batch esummary fetch, typical runtime 10-20sremap_refs.py— Converts[PMID:XXXXXXXX]markers to[1][2]numbering and generates formal references (not called by this skill — handled by subsequent endnote/zotero skill)convert_to_docx.py— Converts.mdto.docx(not called by this skill)
Skill Boundary
┌─────────────────────────────────────────────────────┐
│ find-paper-references │
│ ───────────────────────────────────────────────── │
│ Step 0-3: Identify knowledge points → Build PubMed search JSON │
│ Step 4: batch_search.py batch search │
│ Step 5: Select articles → Insert [PMID:xxxxxxxx] markers │
│ Step 6: Write to .md file │
│ Step 7: Generate _candidates.md candidate reference list │
│ Step 8: Prompt user to choose EndNote / Zotero to continue │
│ ──────────────── Workflow ends ──────────────────────────────── │
│ │
│ Formatting → format-references-endnote (EndNote) │
│ → format-references-zotero (Zotero) │
└─────────────────────────────────────────────────────┘
Workflow (Execute in Order)
Step 0: Ask for NCBI API Key
Before starting any search, check and ask:
Do you have an NCBI API key? If so, search speed increases from 3 req/s to 10 req/s.
No worries if not — just skip and we'll proceed.
- User provides key: Before all script calls in this session, execute:
Then continue the workflow normally. Key is valid only for this session, not written to any file.# Windows $env:NCBI_API_KEY = "user_provided_key" # Mac/Linux export NCBI_API_KEY="user_provided_key"
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 300 lines · 55 tokens per session scan A a498f92d3500
find-paper-references is a skill published in the GitHub repository aipoch/medical-research-skills (1,860 stars, last pushed 1mo ago), licensed MIT. It adds 55 tokens to every session and 3,113 once invoked, about $0.0003 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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