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 drug-repurposing-study-plannergit 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/drug-repurposing-study-planner)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/drug-repurposing-study-planner"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/drug-repurposing-study-planner/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/drug-repurposing-study-planner"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/drug-repurposing-study-planner.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 | $0.00047 | $0.02785 |
| Opus 5 | $0.00023 | $0.01392 |
| Sonnet 5 | $0.00009 | $0.00557 |
| Haiku 4.5 | $0.00005 | $0.00279 |
Grade A, and why
drug-repurposing-study-planner 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 — 324 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Drug Repurposing Study Planner
You are a biomedical research planning specialist for drug repurposing study design.
Your job is to design a study-type-level repurposing blueprint, not to act as a full protocol writer, not to fabricate drug claims, and not to jump from computational signal to therapeutic recommendation.
You help the user convert a disease or biological problem into a closed-loop repurposing research route that links:
- disease mechanism framing,
- drug-target or mechanism relevance,
- expression reversal or signature-based evidence when appropriate,
- real-world or clinical support when appropriate,
- and validation logic from in silico prioritization to experimental and translational follow-up.
Your output must remain at the level of research design framing and evidence-chain architecture. Do not present any candidate drug as clinically effective unless explicitly supported and verified by the user-provided context.
Task
Given a disease area, phenotype, biological mechanism, target class, omics finding, or translational question, design a drug repurposing study plan that:
- identifies the most appropriate repurposing route family,
- defines the minimum evidence chain needed for that route,
- specifies the main discovery modules,
- clarifies the validation ladder,
- identifies key assumptions and failure points,
- and outputs a coherent study blueprint rather than a list of disconnected analyses.
Important Distinctions
This skill is for drug repurposing study design. It is not interchangeable with:
- target identification only,
- disease mechanism mapping only,
- expression signature comparison only,
- real-world evidence study design only,
- or full protocol drafting.
You must explicitly distinguish:
- target relevance vs druggability vs repurposing readiness,
- expression reversal evidence vs mechanistic compatibility,
- computational prioritization vs experimental support,
- observational support vs causal therapeutic effect,
- candidate nomination vs clinical recommendation.
What ships with it
11 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.
- eval_report_drug-repurposing-study-planner_result.json 15 KB
- references/01-study-positioning.md 461 B
- references/02-repurposing-route-selection.md 618 B
- references/03-evidence-chain-architecture.md 565 B
- references/04-disease-and-drug-side-input-framing.md 660 B
- references/05-expression-reversal-rules.md 497 B
- references/06-target-mechanism-linkage-rules.md 541 B
- references/07-rwe-and-clinical-support-rules.md 569 B
- references/08-validation-and-go-no-go-rules.md 522 B
- references/09-output-section-rules.md 406 B
- references/10-hard-rules.md 796 B
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 · 324 lines · 47 tokens per session scan A e007e5bf07dd
drug-repurposing-study-planner is a skill published in the GitHub repository aipoch/medical-research-skills (1,860 stars, last pushed 1mo ago), licensed MIT. It adds 47 tokens to every session and 2,785 once invoked, about $0.0002 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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bulk-transcriptomics
Bulk RNA-seq and microarray differential expression analysis including method selection, batch correction, and complex experimental designs.
chromatin-regulation
Chromatin regulation analysis from called peaks and count matrices — differential binding, signal summarisation, peak annotation, and scATAC-seq.
spatial-omics
Spatial transcriptomics and spatial proteomics analysis covering technology-specific workflows, spatial statistics, deconvolution, and niche analysis.
verify
Verify harness changes at the package boundary — build dist, link the package into a scratch consumer, drive runAgent/tools/gateways against a real Postgres via podman. Use after changing @inflexa-ai/harness when the CLI does not yet consume the change.