How do I install the Drug Retrosynthesis skill?

Run npx skillmds@latest add learningmatter-mit/drug-retrosynthesis in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Drug Retrosynthesis safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: executes scripts, makes network calls, reads secrets. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Drug Retrosynthesis?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Drug Retrosynthesis free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Drug Retrosynthesis?

learningmatter-mit (@learningmatter-mit) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Drug Retrosynthesis by learningmatter-mit

Name: Drug Retrosynthesis
Rating: 4.2 (5 reviews)
Author: learningmatter-mit

File contents

drug-retrosynthesis

Goal

To predict the retrosynthetic pathways and synthetic accessibility of novel small molecules (such as undocumented fluorinated gases) using the state-of-the-art transformer models provided by IBM RXN for Chemistry.

Instructions

1. Identify Target Molecule

Ensure you have the valid canonical SMILES string for the target material or chemical you wish to synthesize.

2. Set Up the IBM RXN Environment

Because IBM RXN is a cloud-hosted API, you must have an API Key.

Sign up for a free IBM RXN account at https://rxn.res.ibm.com/
Generate an API Key in your user profile.
Export the key in your terminal session before running the skill script:

export RXN_API_KEY="your-api-key-here"

3. Run Retrosynthesis Evaluation

Use the wrapper script to submit the SMILES string to the IBM RXN API. The script will poll the server and return the predicted pathway and a confidence score for synthetic feasibility.

# Env: drugdisc-agent
python .agents/skills/drug-retrosynthesis/scripts/evaluate_ibm_rxn.py "target_smiles" --steps 3

Examples

Evaluating the synthetic pathway for a fluorinated gas analog (e.g., 2,3,3,3-tetrafluoropropene: FC(F)(F)C(F)=C):

# Env: drugdisc-agent
export RXN_API_KEY="api-key-here"
python .agents/skills/drug-retrosynthesis/scripts/evaluate_ibm_rxn.py "FC(F)(F)C(F)=C" --steps 3

Constraints

Environments: Requires the drugdisc-agent conda environment.
Dependencies: The script relies on the rxn4chemistry python library (pip install rxn4chemistry). If not installed, the script will gracefully exit with instructions.
Rate Limits: The IBM RXN free tier has API limits. Do not use this in a high-throughput loop for thousands of molecules without a premium tier.
Sourcing Constraints: This tool does not directly check commercial availability of the proposed precursors. You must manually verify if the starting materials proposed by IBM RXN are commercially available.

References

Schwaller, P. et al., "Predicting retrosynthetic pathways using a combined linguistic model and hyper-graph exploration strategy," Chemical Science, 2020. DOI:10.1039/C9SC05033H
IBM RXN for Chemistry: https://rxn.res.ibm.com/

Author: Sathya Edamadaka Contact: GitHub @snme

---name: drug-retrosynthesisdescription: Predict synthetic accessibility and retrosynthetic pathways for novel molecules using the IBM RXN API.---# drug-retrosynthesis## GoalTo predict the retrosynthetic pathways and synthetic accessibility of novel small molecules (such as undocumented fluorinated gases) using the state-of-the-art transformer models provided by IBM RXN for Chemistry.## Instructions### 1. Identify Target MoleculeEnsure you have the valid canonical SMILES string for the target material or chemical you wish to synthesize.### 2. Set Up the IBM RXN EnvironmentBecause IBM RXN is a cloud-hosted API, you must have an API Key.1. Sign up for a free IBM RXN account at https://rxn.res.ibm.com/2. Generate an API Key in your user profile.3. Export the key in your terminal session before running the skill script:```bashexport RXN_API_KEY="your-api-key-here"```### 3. Run Retrosynthesis EvaluationUse the wrapper script to submit the SMILES string to the IBM RXN API. The script will poll the server and return the predicted pathway and a confidence score for synthetic feasibility.```bash# Env: drugdisc-agentpython .agents/skills/drug-retrosynthesis/scripts/evaluate_ibm_rxn.py "target_smiles" --steps 3```## ExamplesEvaluating the synthetic pathway for a fluorinated gas analog (e.g., 2,3,3,3-tetrafluoropropene: `FC(F)(F)C(F)=C`):```bash# Env: drugdisc-agentexport RXN_API_KEY="api-key-here"python .agents/skills/drug-retrosynthesis/scripts/evaluate_ibm_rxn.py "FC(F)(F)C(F)=C" --steps 3```## Constraints- **Environments**: Requires the `drugdisc-agent` conda environment.- **Dependencies**: The script relies on the `rxn4chemistry` python library (`pip install rxn4chemistry`). If not installed, the script will gracefully exit with instructions.- **Rate Limits**: The IBM RXN free tier has API limits. Do not use this in a high-throughput loop for thousands of molecules without a premium tier.- **Sourcing Constraints**: This tool does not directly check commercial availability of the proposed precursors. You must manually verify if the starting materials proposed by IBM RXN are commercially available.## References- Schwaller, P. et al., "Predicting retrosynthetic pathways using a combined linguistic model and hyper-graph exploration strategy," *Chemical Science*, 2020. [DOI:10.1039/C9SC05033H](https://doi.org/10.1039/c9sc05033h)- IBM RXN for Chemistry: https://rxn.res.ibm.com/---**Author:** Sathya Edamadaka**Contact:** [GitHub @snme](https://github.com/snme)

Frequently asked questions

Drug Retrosynthesis