install
source · Clone the upstream repo
git clone https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/biomni-research-agent" ~/.claude/skills/freedomintelligence-openclaw-medical-skills-biomni-research-agent && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/biomni-research-agent" ~/.openclaw/skills/freedomintelligence-openclaw-medical-skills-biomni-research-agent && rm -rf "$T"
manifest:
skills/biomni-research-agent/SKILL.mdsource content
<!--
# COPYRIGHT NOTICE
# This file is part of the "Universal Biomedical Skills" project.
# Copyright (c) 2026 MD BABU MIA, PhD <md.babu.mia@mssm.edu>
# All Rights Reserved.
#
# This code is proprietary and confidential.
# Unauthorized copying of this file, via any medium is strictly prohibited.
#
# Provenance: Authenticated by MD BABU MIA
-->
name: biomni-research-agent description: Bio-Research Generalist license: MIT metadata: author: Stanford (Snap Lab) source: "https://github.com/snap-stanford/Biomni" version: "1.0.0" compatibility:
- system: Python 3.9+ allowed-tools:
- run_shell_command
- web_fetch
- python_repl keywords:
- biomni
- automation
- biomedical
- reasoning
- tools measurable_outcome: Execute complex research tasks with >95% success rate and validated tool usage.
Biomni (General Biomedical Agent)
A general-purpose biomedical AI agent capable of executing complex research workflows using over 150 tools and databases.
Biomni is a "General-Purpose" biomedical agent. Unlike specialized skills (e.g., just for folding proteins), Biomni acts as a high-level orchestrator that can break down complex open-ended research questions into solvable sub-tasks using a vast library of tools.
When to Use This Skill
- Complex Questions: "What are the potential drug targets for Alzheimer's related to mitochondrial dysfunction?"
- Multi-Step Research: Tasks requiring literature search, data retrieval, and analysis in sequence.
- Exploratory Analysis: When the exact path to the answer isn't known and requires "reasoning."
Core Capabilities
- Tool Use: Access to 150+ tools, 105 software packages, and 59 databases.
- Hypothesis Generation: Can formulate scientific hypotheses and plan experiments to test them.
- Plan & Execute: Breaks down queries into a dependency graph of tasks.
- Database QA: High accuracy (74.4%) in querying biomedical databases.
Workflow
- Query Parsing: The agent analyzes the user's natural language request.
- Tool Selection: It selects relevant tools (e.g., "Search GWAS Catalog", "Run GO Enrichment", "Fetch Uniprot Data").
- Execution Loop:
- Step 1: Get data.
- Step 2: Analyze data.
- Step 3: Refine plan based on intermediate results.
- Synthesis: Combines all findings into a comprehensive answer.
Example Usage
User: "Identify genes associated with Type 2 Diabetes that are also expressed in the pancreas and have approved drugs."
Agent Action:
- Tool:
-> Get T2D associated genes.OpenTargets - Tool:
-> Filter for high expression in Pancreas.GTEx - Tool:
-> Intersect with drug targets.DrugBank - Result: Returns a list of genes (e.g., GLP1R, DPP4) and their drugs.