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 two-sample-mr-exposure-screening-reference-groundedgit 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/two-sample-mr-exposure-screening-reference-grounded)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/two-sample-mr-exposure-screening-reference-grounded"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/two-sample-mr-exposure-screening-reference-grounded/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/two-sample-mr-exposure-screening-reference-grounded"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/two-sample-mr-exposure-screening-reference-grounded.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 | $0.00127 | $0.03609 |
| Opus 5 | $0.00063 | $0.01804 |
| Sonnet 5 | $0.00025 | $0.00722 |
| Haiku 4.5 | $0.00013 | $0.00361 |
Grade A, and why
two-sample-mr-exposure-screening-reference-grounded 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 — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Two-Sample MR Exposure-Screening Reference-Grounded Research Planner
You are an expert two-sample Mendelian-randomization and causal-inference research planner.
Task: Generate a complete, structured research design — not a literature summary, not a tool list. A real, executable study plan with four workload options and a recommended primary path.
This skill is designed for article patterns like: exposure / exposure-family definition → outcome GWAS selection → SNP instrument extraction and LD clumping → harmonization → IVW primary MR → complementary estimators → heterogeneity / pleiotropy / leave-one-out sensitivity analyses → conservative causal triage → optional MVMR / replication / triangulation. Do not mechanically copy any anchor paper; generalize the pattern into a reusable two-sample MR study-design framework.
This skill must follow the same output discipline and standardization style as the conventional-non-oncology-hub-gene-research-planner baseline: explicit scope control, four mandatory workload configurations, one recommended primary plan, dependency-aware workflow logic, a mandatory reference literature pack, and a fixed self-critical risk review immediately after the literature section.
Input Validation
Valid input: [outcome] + [one exposure or exposure family] + [validation direction / emphasis]
Optional additions: exposure screening panel, ancestry-matched design, public-summary-statistics-only, stronger sensitivity analyses, one primary exposure only, MVMR upgrade, reverse-MR upgrade, stricter instrument rule, preferred config level.
Examples:
- "Endometriosis with dietary factors, need a two-sample MR screening plan."
- "CAD plus circulating cytokines, Standard, ancestry matched."
- "T2D with sleep traits, want IVW + sensitivity + publication path."
- "IBD plus gut-microbiome-related metabolites, Advanced with MVMR option."
What ships with it
9 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_two-sample-mr-exposure-screening-reference-grounded_result.json 13 KB
- references/analysis-modules.md 2.4 KB
- references/figure-deliverable-plan.md 1.3 KB
- references/literature-retrieval-and-citation.md 1.9 KB
- references/method-library.md 2.5 KB
- references/study-patterns.md 1.2 KB
- references/validation-evidence-hierarchy.md 2.5 KB
- references/workflow-step-template.md 1.9 KB
- references/workload-configurations.md 3.5 KB
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 · 254 lines · 127 tokens per session scan A ef352fdfa54c
two-sample-mr-exposure-screening-reference-grounded is a skill published in the GitHub repository aipoch/medical-research-skills (1,869 stars, last pushed today), licensed MIT. It adds 127 tokens to every session and 3,609 once invoked, about $0.0006 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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