Molecular Complexity-related Properties Calculation
SkillMonitoring & opsCompute 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.
No other account needed.
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-transferbefore execution. - For PDB file inputs, it is recommended to preprocess them using
molclaw-pdbfixerbefore execution. - Please refer to skill
molclaw-scp-serverto 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