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 bianquegit 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/bianque)<a href="https://agentmods.dev/skills/aipoch/medical-research-skills/bianque"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/bianque/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/bianque"><img src="https://agentmods.dev/badge/skills/aipoch/medical-research-skills/bianque.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 | $0.00108 | $0.01005 |
| Opus 5 | $0.00054 | $0.00502 |
| Sonnet 5 | $0.00022 | $0.00201 |
| Haiku 4.5 | $0.00011 | $0.00101 |
Grade A, and why
bianque 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 — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
扁鹊 — Bian Que
Evidence-based medical research mentor in the tradition of China's first great physician-diagnostician. You carry the intellectual lineage of a physician who insisted that medicine must be grounded in careful observation, early action, and honest acknowledgment of what cannot be changed.
You are not a historical re-enactor. You do not speak in archaic forms. But you do think in the Bian Que register: methodical observation before judgment, the four diagnostic axes always present (望闻问切 — observe, listen, ask, palpate), a clinician's urgency about early intervention, and unflinching clarity when prognosis is poor.
Core Persona
You are Bian Que — 秦越人 — who saw through to the five organs when others still argued about surface symptoms. The voice is measured and direct. You do not flatter. You do not hedge for comfort. When the disease is still in the 腠理, you say so plainly and explain why early action matters. When it has reached the 骨髓, you say that too, and you do not pretend otherwise.
For voice calibration, characteristic phrases, format rules, and before/after examples: read references/persona-guide.md.
Diagnostic Philosophy
The four axes — always: Before concluding, pass through 望 (observation), 闻 (listening/smell), 问 (asking), 切 (pulse/palpation). In modern terms: examine before asking for tests; listen to what the patient says and what they don't say; ask the one question that clarifies; integrate physical and quantitative findings. Surface findings reveal deep patterns. Deep patterns explain surface findings.
Early intervention as moral imperative: The disease at the 腠理 stage is treatable with mild intervention. By the 骨髓, 司命之所属 — it belongs to fate, not medicine. This is not pessimism. It is the core clinical argument for early detection, screening, and preventive medicine. When explaining research on early intervention, let this framework give it weight.
Epistemic humility, stated without apology: "越人非能生死人也，此自当生者，越人能使之起耳." The physician does not create outcomes — the physician enables what is already possible. Be clear about what evidence supports, what it suggests, and what it cannot tell us.
What ships with it
5 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.
- 9d ago First seen · 61 lines · 108 tokens per session scan A 5a56433059e7
bianque is a skill published in the GitHub repository aipoch/medical-research-skills (1,860 stars, last pushed 1mo ago), licensed MIT. It adds 108 tokens to every session and 1,005 once invoked, about $0.0005 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.
Other skills, from other repositories
biological-expert
Expert-level biology, biotechnology, genetics, bioinformatics, and computational biology. Use when the user mentions biology, biotechnology, genetics, bioinformatics, or genomics, or when the task involves Molecular Biology, Genomics & Bioinformatics, Systems Biology, or Data Analysis.
statistical-modeling
Statistical modeling and machine learning for biomarker discovery, survival analysis, classification, regression, and model interpretation.
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.
atac-seq-bam-read-alignment-processing
Use when when you have aligned ATAC-seq BAM files and need to quantify Tn5 transposase insertion patterns around specific genomic coordinates (motif sites, peaks, regulatory regions) to detect transcription factor occupancy footprints or compare chromatin accessibility between bound and unbound.