| name | medea-therapeutic-discovery |
| description | An AI agent for therapeutic discovery that executes transparent, multi-step omics analyses including research planning, code execution, and literature reasoning. |
| license | MIT |
| metadata | {"author":"Artificial Intelligence Group (Adapted from openscientist.ai)","version":"1.0.0"} |
| compatibility | [{"system":"Python 3.10+"}] |
| allowed-tools | ["run_shell_command","read_file","web_fetch"] |
Medea Therapeutic Discovery Agent
Medea is a multi-stage AI agent designed for therapeutic discovery, modeled after 2026 state-of-the-art open source architectures. It executes transparent, multi-step omics analyses.
When to Use This Skill
- "Run multi-omics therapeutic discovery pipeline"
- "Analyze omics data for novel drug targets using Medea"
- "Perform literature reasoning and consensus reconciliation for target X"
Core Capabilities
- Research Planning: Formulates step-by-step omics analysis plans.
- Code Execution: Generates and executes Python/R scripts for data processing.
- Literature Reasoning: Retrieves and synthesizes current literature.
- Consensus Stage: Reconciles experimental evidence with literature to propose high-confidence targets.
Workflow
- Step 1: Initialize Medea agent with target disease or omics dataset.
- Step 2: Execute the multi-stage pipeline across planning, coding, literature review, and consensus validation.
Example Usage
User: "Run Medea analysis on the provided breast cancer multi-omics dataset."
Agent Action:
python3 -m medea.agent --dataset breast_cancer_omics.h5ad --mode full_discovery