Rdkit Molecular Descriptors
Use this skill to compute compact cheminformatics descriptors from one SMILES string with RDKit. Do not use it for docking, quantum chemistry, or large library screening.
Install
$ agentstack add skill-ma-compbio-lab-skillfoundry-rdkit-molecular-descriptors ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-ma-compbio-lab-skillfoundry-rdkit-molecular-descriptors) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Purpose
Turn a SMILES string into a compact descriptor summary suitable for quick triage, featurization, and metadata enrichment.
When to use
- You need a local RDKit-backed molecular summary from a SMILES string.
- You want canonical SMILES, formula, weight, and simple physicochemical descriptors.
When not to use
- You need conformer generation, docking, or reaction modeling.
- You need batch-scale descriptor computation for millions of compounds.
Inputs
- One SMILES string
- Optional molecule name
- Optional JSON output path
Outputs
- JSON summary with canonical SMILES, formula, exact mass, logP, TPSA, HBA/HBD, rotatable bonds, ring count, and heavy-atom count
Requirements
slurm/envs/chem-toolswith RDKit available
Procedure
- Run
slurm/envs/chem-tools/bin/python skills/drug-discovery-and-cheminformatics/rdkit-molecular-descriptors/scripts/compute_rdkit_descriptors.py --smiles "CC(=O)OC1=CC=CC=C1C(=O)O" --name aspirin. - Inspect
canonical_smiles,formula,molecular_weight, andtpsa. - Reuse the JSON payload for downstream filtering or reporting.
Validation
- The command exits successfully.
canonical_smilesis non-empty for a known valid molecule.- Descriptor fields are numeric where expected.
Failure modes and fixes
- Invalid SMILES: verify the input string and quoting.
- Missing RDKit environment: run the script with
slurm/envs/chem-tools/bin/python.
Safety and limits
- Descriptor calculation only.
- No medicinal-chemistry or safety interpretation is implied.
Provenance
- RDKit docs: https://www.rdkit.org/docs/index.html
- RDKit repository: https://github.com/rdkit/rdkit
Related skills
chembl-molecule-search
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: ma-compbio-lab
- Source: ma-compbio-lab/SkillFoundry
- License: Apache-2.0
- Homepage: https://ma-compbio-lab.github.io/SkillFoundry/
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.