Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing.
1,855
stars
198
commits
Python
primary language
Jul 15, 2026
updated
A curated library of 550+ medical research agent skills created by AIPOCH, designed to work with Claude Code, Codex, Open Code, Hermes Agent, OpenClaw, and other SKILL.md-compatible agent platforms. It supports the research workflow across four core areas: Evidence Insights, Protocol Design, Data Analysis, and Academic Writing. Built exclusively for medical and biomedical researchers. Every skill in this library is reviewed and evaluated through MedSkillAudit— A Domain-Specific Audit Framework for Medical Research Agent Skills — before going live. Equip your AI agent with AIPOCH medical research skills, and turn it into a capable medical research assistant.
⭐ Star this repo — the library is actively maintained and grows with new skills, improvements, and fixes regularly. Hit the star button to keep it close, stay current with the latest releases, and help more researchers discover Medical Research Agent Skills. Every star directly supports the continued development of this library.
💡New: We are launching Open Science, an open-source, model-agnostic AI workbench designed to support scientific discovery workflows. Learn more
MedSkillAudit - a domain-specific audit framework for medical research agent skills. Try skill-auditor here.
All skills in AIPOCH are originally designed and developed in-house, built to reflect medical research workflows and standards. The library is primarily organized into five categories: Evidence Insights, Protocol Design, Data Analysis, Academic Writing, and Others.
| 📚Category | Highlights |
|---|---|
| 🔍 Evidence Insight | e.g., search strategy design, database selection, evidence-level prioritization, critical appraisal, literature synthesis and gap identification. |
| 🧪 Protocol Design | e.g., experimental design generation, study type selection, causal inference planning, statistical power calculation, validation strategy. |
| 📊 Data Analysis | e.g., R/Python bioinformatics code generation, statistical modeling, data cleaning pipelines, machine learning workflows, result visualization. |
| ✍️ Academic Writing | e.g., SCI manuscript drafting, methods/results/discussion writing, meta-analysis narrative, cover letters, abstract generation. |
| 🌍 Other (General / Non-Research) | all general skills that do not fall into categories 1–4. |
📌 Total Skills in Library: 554 and growing
Before a study begins, researchers need to know what is already established, where the evidence is weak, and where the genuine gaps are. This category covers the full evidence pipeline: building precision search strategies across PubMed and multiple databases, screening literature at scale, reading papers with methodological depth, mapping the evidence landscape around a disease or biomarker, and identifying research gaps with an evidence audit trail.
Moving from a research question to a submission-ready protocol requires choosing the right study architecture, controlling for bias sources, and justifying every design decision to reviewers and ethics boards. This category provides hypothesis formulation tools, study design selectors, sample size calculators, and 30+ disease- and method-specific study planners that generate full protocol drafts grounded in current methodological standards.
From raw sequencing files to interpretable biological findings, these skills cover single-cell RNA-seq, bulk transcriptomics, multi-omics integration, genomics, proteomics, and microbiome workflows — with outputs formatted for direct inclusion in manuscript figures and methods sections.
Clinical and translational research demands statistical rigor across every phase — from systematic review registration and literature screening through survival modeling, diagnostic accuracy evaluation, and clinical prediction model validation. This category covers the complete meta-analysis workflow with 15+ figure types, plus the full range of clinical statistical methods used in SCI-indexed medical journals.
Computational workflows for medicinal chemistry, molecular biology, and translational pharmacology research — from virtual screening and molecular docking through network pharmacology and systems toxicology.
Structured writing assistance for every stage of a medical manuscript — from first draft through peer review response and resubmission. These skills support researchers in organizing their findings, meeting reporting standards, and preparing submission-ready documents. All outputs require researcher review and judgment before use.
Built for clinical researchers and educators who need structured research-context documentation, data privacy tools, and medical education content.
The operational layer of a medical research lab — from reagent tracking and figure production to reproducibility auditing, document generation, and research administration.
Host Platform: OpenClaw (installed and running) or any compatible AI Agent framework that supports Skill integration.
If you don't have OpenClaw, please follow the official OpenClaw setup guide.
Git: Required for cloning the repository. Git LFS
I'm a human
curl -sL https://aipoch.com/skill.md > ./skills/aipoch.md
I'm an agent
Read https://aipoch.com/skill.md and follow the instructions to join Aipoch
🦞 Install into OpenClaw Plug-in
OpenClaw is a self-hosted AI agent gateway. You can install all AIPOCH skills into OpenClaw with a single command.
macOS / Linux / WSL:
bash <(curl -s https://raw.githubusercontent.com/aipoch/medical-research-skills/main/scientific-skills/scripts/openclaw-install.sh)
Windows (Git Bash):
curl -s https://raw.githubusercontent.com/aipoch/medical-research-skills/main/scientific-skills/scripts/openclaw-install.sh -o /tmp/install.sh
bash /tmp/install.sh
The script will:
SKILL.md skill folders into ~/.openclaw/skills/After installation, restart your gateway to pick up the new skills:
openclaw gateway restart
Tip: Run with
--dry-runfirst to preview what will be installed without making any changes.bash <(curl -s https://raw.githubusercontent.com/aipoch/medical-research-skills/main/scientific-skills/scripts/openclaw-install.sh) --dry-run
Note: Skills are installed to
~/.openclaw/skills/by default (visible to all agents). To install into a specific workspace instead, set the environment variable before running:OPENCLAW_SKILLS_DIR=~/.openclaw/workspace/skills bash <(curl -s https://raw.githubusercontent.com/aipoch/medical-research-skills/main/scientific-skills/scripts/openclaw-install.sh)
A brief showcase of AIPOCH Medical Research Skills in action across research workflows.
Awesome Med Research Skills is a curated collection of medical research Agent Skills, currently including 140 high-quality skills.
We aim to help researchers more effectively organize questions, connect evidence, and advance research. To achieve this, we encode professional medical research logic into these agent skills:
The examples below represent selected skills from each category.
Python
78.8%
R
14.7%
TeX
3.7%
JavaScript
2.1%
Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing.
1,855
stars
198
commits
Python
primary language
Jul 15, 2026
updated
A curated library of 550+ medical research agent skills created by AIPOCH, designed to work with Claude Code, Codex, Open Code, Hermes Agent, OpenClaw, and other SKILL.md-compatible agent platforms. It supports the research workflow across four core areas: Evidence Insights, Protocol Design, Data Analysis, and Academic Writing. Built exclusively for medical and biomedical researchers. Every skill in this library is reviewed and evaluated through MedSkillAudit— A Domain-Specific Audit Framework for Medical Research Agent Skills — before going live. Equip your AI agent with AIPOCH medical research skills, and turn it into a capable medical research assistant.
⭐ Star this repo — the library is actively maintained and grows with new skills, improvements, and fixes regularly. Hit the star button to keep it close, stay current with the latest releases, and help more researchers discover Medical Research Agent Skills. Every star directly supports the continued development of this library.
💡New: We are launching Open Science, an open-source, model-agnostic AI workbench designed to support scientific discovery workflows. Learn more
MedSkillAudit - a domain-specific audit framework for medical research agent skills. Try skill-auditor here.
All skills in AIPOCH are originally designed and developed in-house, built to reflect medical research workflows and standards. The library is primarily organized into five categories: Evidence Insights, Protocol Design, Data Analysis, Academic Writing, and Others.
| 📚Category | Highlights |
|---|---|
| 🔍 Evidence Insight | e.g., search strategy design, database selection, evidence-level prioritization, critical appraisal, literature synthesis and gap identification. |
| 🧪 Protocol Design | e.g., experimental design generation, study type selection, causal inference planning, statistical power calculation, validation strategy. |
| 📊 Data Analysis | e.g., R/Python bioinformatics code generation, statistical modeling, data cleaning pipelines, machine learning workflows, result visualization. |
| ✍️ Academic Writing | e.g., SCI manuscript drafting, methods/results/discussion writing, meta-analysis narrative, cover letters, abstract generation. |
| 🌍 Other (General / Non-Research) | all general skills that do not fall into categories 1–4. |
📌 Total Skills in Library: 554 and growing
Before a study begins, researchers need to know what is already established, where the evidence is weak, and where the genuine gaps are. This category covers the full evidence pipeline: building precision search strategies across PubMed and multiple databases, screening literature at scale, reading papers with methodological depth, mapping the evidence landscape around a disease or biomarker, and identifying research gaps with an evidence audit trail.
Moving from a research question to a submission-ready protocol requires choosing the right study architecture, controlling for bias sources, and justifying every design decision to reviewers and ethics boards. This category provides hypothesis formulation tools, study design selectors, sample size calculators, and 30+ disease- and method-specific study planners that generate full protocol drafts grounded in current methodological standards.
From raw sequencing files to interpretable biological findings, these skills cover single-cell RNA-seq, bulk transcriptomics, multi-omics integration, genomics, proteomics, and microbiome workflows — with outputs formatted for direct inclusion in manuscript figures and methods sections.
Clinical and translational research demands statistical rigor across every phase — from systematic review registration and literature screening through survival modeling, diagnostic accuracy evaluation, and clinical prediction model validation. This category covers the complete meta-analysis workflow with 15+ figure types, plus the full range of clinical statistical methods used in SCI-indexed medical journals.
Computational workflows for medicinal chemistry, molecular biology, and translational pharmacology research — from virtual screening and molecular docking through network pharmacology and systems toxicology.
Structured writing assistance for every stage of a medical manuscript — from first draft through peer review response and resubmission. These skills support researchers in organizing their findings, meeting reporting standards, and preparing submission-ready documents. All outputs require researcher review and judgment before use.
Built for clinical researchers and educators who need structured research-context documentation, data privacy tools, and medical education content.
The operational layer of a medical research lab — from reagent tracking and figure production to reproducibility auditing, document generation, and research administration.
Host Platform: OpenClaw (installed and running) or any compatible AI Agent framework that supports Skill integration.
If you don't have OpenClaw, please follow the official OpenClaw setup guide.
Git: Required for cloning the repository. Git LFS
I'm a human
curl -sL https://aipoch.com/skill.md > ./skills/aipoch.md
I'm an agent
Read https://aipoch.com/skill.md and follow the instructions to join Aipoch
🦞 Install into OpenClaw Plug-in
OpenClaw is a self-hosted AI agent gateway. You can install all AIPOCH skills into OpenClaw with a single command.
macOS / Linux / WSL:
bash <(curl -s https://raw.githubusercontent.com/aipoch/medical-research-skills/main/scientific-skills/scripts/openclaw-install.sh)
Windows (Git Bash):
curl -s https://raw.githubusercontent.com/aipoch/medical-research-skills/main/scientific-skills/scripts/openclaw-install.sh -o /tmp/install.sh
bash /tmp/install.sh
The script will:
SKILL.md skill folders into ~/.openclaw/skills/After installation, restart your gateway to pick up the new skills:
openclaw gateway restart
Tip: Run with
--dry-runfirst to preview what will be installed without making any changes.bash <(curl -s https://raw.githubusercontent.com/aipoch/medical-research-skills/main/scientific-skills/scripts/openclaw-install.sh) --dry-run
Note: Skills are installed to
~/.openclaw/skills/by default (visible to all agents). To install into a specific workspace instead, set the environment variable before running:OPENCLAW_SKILLS_DIR=~/.openclaw/workspace/skills bash <(curl -s https://raw.githubusercontent.com/aipoch/medical-research-skills/main/scientific-skills/scripts/openclaw-install.sh)
A brief showcase of AIPOCH Medical Research Skills in action across research workflows.
Awesome Med Research Skills is a curated collection of medical research Agent Skills, currently including 140 high-quality skills.
We aim to help researchers more effectively organize questions, connect evidence, and advance research. To achieve this, we encode professional medical research logic into these agent skills:
The examples below represent selected skills from each category.
Python
78.8%
R
14.7%
TeX
3.7%
JavaScript
2.1%