Chemical property lookup
Skill FridrichMethod/awesome-skills/skills/chemical-property-lookup
Compute RDKit-driven molecular properties (MW, logP, TPSA, QED, Lipinski) for a SMILES string to support downstream drug discovery tools.From its SKILL.md
npx -y skills add FridrichMethod/awesome-skills --skill chemical-property-lookupAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
1.5 KB, 344 tokens by cl100k_base, as published. Nobody here has run it
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# Copyright (c) 2026 MD BABU MIA, PhD <[email protected]>
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At-a-Glance
- description (10-20 chars): RDKit stats
- keywords: SMILES, RDKit, Lipinski, QED, ADMET
- measurable_outcome: Return a validated property summary (JSON + Lipinski verdict) for each SMILES within 60 seconds of request.
Workflow
- Validate SMILES input; raise explicit errors for invalid syntax.
- Call helpers from
molecular_tools.py(summarize_properties,check_lipinski, etc.). - Report MW, logP, TPSA, HBD/HBA, QED, and Lipinski pass/fail with violations.
- Surface any calculation warnings (e.g., aromaticity perception issues).
Guardrails
- Never infer stereochemistry; report as "not provided".
- Log invalid SMILES for manual follow-up.
- Communicate that results are screening heuristics, not definitive ADMET outcomes.
References
README.mdplusmolecular_tools.pyfor function signatures and dependencies.
What ships with it: 2 files
7.3 KB alongside SKILL.md, 1 of them executable
- molecular_tools.pyruns5.1 KB
- README.md2.2 KB