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.
git 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/commands/aipoch/medical-research-skills/update)<a href="https://agentmods.dev/commands/aipoch/medical-research-skills/update"><img src="https://agentmods.dev/badge/commands/aipoch/medical-research-skills/update/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/commands/aipoch/medical-research-skills/update"><img src="https://agentmods.dev/badge/commands/aipoch/medical-research-skills/update.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 | $0.00000 | $0.00553 |
| Opus 5 | $0.00000 | $0.00277 |
| Sonnet 5 | $0.00000 | $0.00111 |
| Haiku 4.5 | $0.00000 | $0.00055 |
Grade A, and why
update 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 7d 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/update — Update Research Direction
Run when the research direction, methodology, or theoretical framework has changed. Collects the change through conversation and syncs all relevant configuration.
When to Use
- A new research method has been decided (e.g., shifting from qualitative to mixed methods)
- The research question has been narrowed to a more specific focus
- A new theoretical framework has been added
- The research scope has expanded or contracted
- The disease focus or clinical setting has shifted
Steps
1. Show Current Configuration
[Tier C / B] Read memory/MEMORY.md. Show the user a summary of the currently recorded research direction, and confirm this is the baseline they want to modify.
[Tier A] Ask the user to paste their Session Card if not already provided.
2. Understand the Change
Ask:
What aspects have changed? Describe it directly — no formal language needed. For example: "I have now confirmed I am using a retrospective cohort design" or "I am narrowing the focus to only ferroptosis-related lncRNAs in glioblastoma" or "I am adding survival prediction modeling as a second aim."
If the description is vague, ask one follow-up question to clarify. Do not ask multiple questions at once.
3. Update memory/MEMORY.md
Make precise edits to the changed fields only. Do not rewrite the entire document.
- If a new theoretical framework was added, incorporate it into the Key Variables / Framework section or Key Decisions
- If Relevant Journals need adjustment, update them accordingly
- Keep all unchanged sections intact
4. Regenerate search_config.json Search Terms
Based on the updated research direction, regenerate Tier 1 / 2 / 3 search terms:
- Keep terms that are still relevant
- Replace terms that no longer apply
- Add terms reflecting the new direction
- Update
last_updatedandupdate_reason(note that this update was triggered by a research direction change) - Leave
based_on_notesunchanged
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.
- 7d ago First seen · 72 lines · 0 tokens per session scan A 657d7b6d09f3
update is a command published in the GitHub repository aipoch/medical-research-skills (1,848 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 553 tokens. 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.
Other commands, from other repositories
run-gsea
Pathway enrichment on a ranked gene list (GSEA or ORA). Use when the user asks which pathways are enriched, wants GSEA/fgsea, or has DE results to interpret biologically.
analyze-degs
Differential expression from a count matrix with DESeq2. Use when the user has bulk RNA-seq counts and wants DEGs, a volcano plot, or asks which genes differ between conditions.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.