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Chematagent drug discovery

Skill FridrichMethod/awesome-skills/skills/chematagent-drug-discovery

Chemical Lab AgentFrom its SKILL.md

Install
npx -y skills add FridrichMethod/awesome-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.

2 things 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.
  • 13 stars13 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its file declares

Copied from the file, not written here

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

1.8 KB, 367 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 -->

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.

Keep looking

Skills are one crate of 325,949. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.