Molecular Hydrophobicity-related Properties Calculation

SkillMonitoring & ops

Computes hydrophobicity-related molecular descriptors for a given list of SMILES strings, returning the octanol-water partition coefficient (logP) and molar refractivity for each input molecule.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Molecular Hydrophobicity-related Properties Calculation skill

What this skill tells your AI

The instructions your AI receives, as published by internscience/molclaw in skills/L1_tools/molclaw-mol-hydrophobicity-metrics/SKILL.md and read by ahel’s review.

Note:

  • Local files are not directly accessible by the server. Please upload them to the server using molclaw-file-transfer before execution.
  • For PDB file inputs, it is recommended to preprocess them using molclaw-pdbfixer before execution.
  • Please refer to skill molclaw-scp-server to complete tool invocation.

The description of tool calculate_mol_hydrophobicity.

Compute hydrophobicity-related molecular descriptors for each SMILES.
Args:
    smiles_list (List[str]): List of input SMILES strings, (e.g., ["N[C@@H](Cc1ccc(O)cc1)C(=O)O", "CC(C)C1=CC=CC=C1"])
Return:
    status (str): success/error
    msg (str): message
    metrics (List[dict]): List of dict, each containing feature keys.
        --smiles (str): A SMILES string of smiles_list
        --logp (float): The octanol-water partition coefficient (logP)
        --molar_refractivity (float): Molar refractivity

How to use tool calculate_mol_hydrophobicity:

response = await client.session.call_tool(
    "calculate_mol_hydrophobicity",
    arguments={
        "smiles_list": smiles_list
    }
)
result = client.parse_result(response)
metrics = result["metrics"]

Signals

GitHub stars
33
Forks
3
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
molclaw-mol-hydrophobicity-metrics
Source
github.com/internscience/molclaw