Molecular Complexity-related Properties Calculation

SkillMonitoring & ops

Compute custom molecular complexity-related descriptors for a given list of SMILES strings, returning the molecular complexity score, aromatic proportion, and asphericity value 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 Complexity-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-complexity-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_complexity.

Compute custom molecular complexity-related 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
        --molecular_complexity (int): Molecular complexity
        --aromatic_proportion (float): Aromatic proportion
        --asphericity (float): Asphericity

How to use tool calculate_mol_complexity:

response = await client.session.call_tool(
    "calculate_mol_complexity",
    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-complexity-metrics
Source
github.com/internscience/molclaw