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Chematagent drug discovery

Skill BioTender-max/awesome-bio-agent-skills/skills/openclaw/chematagent-drug-discovery

A curated collection of AI agent skills for biomedical research, covering genomics, proteomics, single-cell analysis, clinical AI, and protein design.From the repository description

Install
npx -y skills add BioTender-max/awesome-bio-agent-skills --skill chematagent-drug-discovery

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.

SKILL.md

1.8 KB, 485 tokens by cl100k_base, as published. Nobody here has run it

<!-- # COPYRIGHT NOTICE # This file is part of the "Universal Biomedical Skills" project. # Copyright (c) 2026 MD BABU MIA, PhD <[email protected]> # 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: chematagent-drug-discovery description: Chemical Lab Agent keywords:

  • chemistry
  • drug-discovery
  • tools
  • synthesis
  • property-prediction measurable_outcome: Plan a synthesis route and predict ADMET properties for a candidate molecule with >80% validity. license: MIT metadata: author: CheMatAgent Team version: "1.0.0" compatibility:
  • system: Python 3.9+ allowed-tools:
  • run_shell_command
  • read_file

CheMatAgent

A two-tiered agent system with access to 137 Python-wrapped chemical tools for drug discovery and materials science.

When to Use

  • Molecule Design: Generating novel structures with specific properties.
  • Property Prediction: Estimating solubility, toxicity, and bioactivity.
  • Synthesis Planning: Designing retro-synthetic routes.

Core Capabilities

  1. Tool Orchestration: Manages a library of 137 chemical tools.
  2. Multi-Scale Modeling: Bridges quantum mechanics and molecular dynamics.
  3. Lab Automation: Generates instructions for robotic synthesis platforms.

Workflow

  1. Goal: Define target property (e.g., "LogP < 5").
  2. Design: Generate candidates.
  3. Filter: Use property prediction tools.
  4. Plan: Output synthesis recipe.

Example Usage

User: "Design a molecule similar to Aspirin but with higher solubility."

Agent Action:

python -m chematagent.design --scaffold "Aspirin" --objective "maximize solubility"
<!-- AUTHOR_SIGNATURE: 9a7f3c2e-MD-BABU-MIA-2026-MSSM-SECURE -->

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

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