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 format-references-endnotegit 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/format-references-endnote)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/format-references-endnote"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/format-references-endnote/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/format-references-endnote"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/format-references-endnote.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00066 | $0.01395 |
| Opus 5 | $0.00033 | $0.00698 |
| Sonnet 5 | $0.00013 | $0.00279 |
| Haiku 4.5 | $0.00007 | $0.00139 |
Grade A, and why
format-references-endnote 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 8d 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Medical Literature Reference Formatter
This skill automates the step of turning rough [PMID: xxxx] citation markers into professionally formatted Word documents that work with EndNote's one-click bibliography generation. No COM automation or macros — purely file-based, stable on any machine with Python + Pandoc.
When you're invoked
The user has a Markdown manuscript with inline [PMID: xxxx] markers and wants a .docx with citation placeholders that EndNote can resolve into a formatted bibliography.
Workflow
Step 0 — Check environment (first time or on error)
If this is the first run, or the user reports any unexpected error, run the bundled check script first:
python "<skill_dir>/scripts/check_env.py"
It verifies: Python 3.7+, Pandoc, PubMed API connectivity, EndNote installation, and .ris file association.
If the output shows .ris not associated with EndNote, ask the user: "Would you like to set .ris files to open with EndNote by default? This will allow generated files to trigger automatic import." If they agree, run:
python "<skill_dir>/scripts/check_env.py" --fix-ris
Step 1 — Confirm the target file
If the user didn't specify a full path, ask. If they give a vague location like "on my Desktop", resolve it:
- Windows:
C:\Users\<username>\Desktop\<filename>.md - macOS:
/Users/<username>/Desktop/<filename>.md
Step 2 — Run the bundled processing script
The Python script is at scripts/process_references.py inside this skill's directory. Find the skill directory from the path this SKILL.md was loaded from, then run:
python "<skill_dir>/scripts/process_references.py" "<absolute_path_to_file.md>"
The script handles the entire pipeline: PMID extraction → PubMed API fetch → placeholder substitution → Pandoc compile → RIS generation → auto-open both files.
Caching mechanism: After the first run, a <stem>_pubmed_cache.json file is generated. Subsequent runs automatically reuse the cache to avoid redundant PubMed fetches. When new PMIDs are added, only the new ones are fetched.
What ships with it
4 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.
- 8d ago First seen · 121 lines · 0 tokens per session scan A 5ca4f634f476
format-references-endnote is a skill published in the GitHub repository aipoch/medical-research-skills (1,855 stars, last pushed 1mo ago), licensed MIT. It adds 66 tokens to every session and 1,395 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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