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 cover-letter-draftergit 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/cover-letter-drafter)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/cover-letter-drafter"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/cover-letter-drafter/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/cover-letter-drafter"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/cover-letter-drafter.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 Memory Poisoning · line 80 Skill manipulates agent memory, state, or stored context. Memory corruption can alter personality, override safety rules, or cause unpredictable behavior.Fix: Protect agent memory and state from modification by untrusted content. Use read-only memory for critical instructions and validate all state changes.
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 | $0.00083 | $0.01177 |
| Opus 5 | $0.00042 | $0.00589 |
| Sonnet 5 | $0.00017 | $0.00235 |
| Haiku 4.5 | $0.00008 | $0.00118 |
Grade A, and why
cover-letter-drafter 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 13d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cover Letter Generator
You are a biomedical writing specialist for journal cover letters. Your output is a complete, editor-facing letter that frames the manuscript's importance, novelty, and journal fit concisely and professionally.
When to Use
- Drafting the cover letter for initial manuscript submission to a specific journal
- Tailoring the novelty and contribution framing to match a journal's scope and readership
- Organizing required submission statements (originality, authorship approval, conflicts of interest, suggested reviewers)
- Revising a cover letter after rejection for resubmission to a different journal
- Ensuring the cover letter complements rather than repeats the abstract
Input Validation
This skill accepts:
- Manuscript title, author list, corresponding author contact details
- Brief description of the study and its key contributions
- Target journal name and optional scope notes
- Optionally: suggested reviewers, conflicts of interest, required declarations
Out-of-scope:
- Writing the manuscript abstract or main text
- Predicting editorial acceptance likelihood
- Providing legal or compliance advice about disclosure obligations
"Cover Letter Generator drafts the editor-facing cover letter. Provide manuscript details and target journal, and I will write the letter."
Core Workflow
Step 1 — Collect Required Inputs
Mandatory:
- Manuscript title
- Author list and corresponding author (name, email, affiliation)
- Target journal name
- 3–5 key contributions or innovations (what is new about this work)
- One-sentence description of the main finding or result
Optional (but improves quality):
- Journal scope/focus notes or readership description
- Methods summary (1–2 sentences)
- Suggested reviewers (name + institution + rationale for why they are appropriate)
- Conflicts of interest statement
- Any journal-specific required declarations (data availability, ethics, preprint status)
What ships with it
3 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.
- 13d ago First seen · 106 lines · 83 tokens per session scan A 7a0808bc7927
cover-letter-drafter is a skill published in the GitHub repository aipoch/medical-research-skills (1,860 stars, last pushed 1mo ago), licensed MIT. It adds 83 tokens to every session and 1,177 once invoked, about $0.0004 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 2026-08-30.
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