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 "$T/skills/molecule-evolution-agent" ~/.claude/skills/freedomintelligence-openclaw-medical-skills-molecule-evolution-agent && rm -rf "$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 "$T/skills/molecule-evolution-agent" ~/.openclaw/skills/freedomintelligence-openclaw-medical-skills-molecule-evolution-agent && rm -rf "$T"
manifest:
skills/molecule-evolution-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: 'molecule-evolution-agent' description: 'Evolve Molecules' measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:
- read_file
- run_shell_command
Molecule Evolution Agent
The Molecule Evolution Agent acts as an autonomous medicinal chemist. It takes a starting molecule (or uses a default like Aspirin) and iteratively modifies its structure to optimize binding for a specific protein target.
When to Use This Skill
- Lead Optimization: When you have a hit molecule and want to improve its potency.
- De Novo Design: To explore chemical space around a target protein.
- Idea Generation: To get creative structural modifications suggested by an LLM.
Core Capabilities
- SMILES Manipulation: Reads and writes chemical structures in SMILES format.
- LLM Chemist: Uses an LLM to suggest chemically valid modifications (e.g., "Add a fluorine group to the ring").
- Mock Scoring: (Currently) Uses a mock scoring function to simulate docking affinity.
Workflow
- Input: Target Protein Name (e.g., "GPRC5D").
- Process:
- Start with a seed molecule.
- Loop for N generations.
- Ask LLM for a modification.
- Score the new molecule.
- Keep the best candidate.
- Output: Top candidate SMILES and the evolution history.
Example Usage
User: "Design a better binder for GPRC5D."
Agent Action:
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->python3 Skills/Drug_Discovery/Molecule_Design/evolution_agent.py # (Note: The script currently defaults to GPRC5D, but can be extended for arguments)