--> --- 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 --- A two-tiered agent system with access to 137 Python-wrapped chemical tool...
Scanned 9/8/2026
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---
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**:
```bash
python -m chematagent.design --scaffold "Aspirin" --objective "maximize solubility"
```
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