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RDKit Cheminformatics Toolkit

Lets an agent parse, describe, and search molecules using RDKit, with bundled local scripts

Source Download skill
Repository
K-Dense-AI/scientific-agent-skills
Stars
55,780
Licence
MIT
Files
11 files

What it does

This skill teaches an AI agent to work with chemical structures using RDKit, a widely used open-source chemistry library. Once installed, the agent can read molecules from SMILES or SDF files, calculate properties such as molecular weight, LogP and polar surface area, generate fingerprints, run substructure and similarity searches, and handle reactions and 3D coordinates. It also ships three Python scripts the agent can run locally for property calculation, similarity search, and substructure filtering.

Great for

  • Computational chemists or cheminformatics researchers who want an agent to script RDKit tasks
  • Data scientists screening compound libraries with descriptors and fingerprints
  • Students learning RDKit workflows with worked examples

Skip it if

  • Safety, toxicity, or potency decisions: the skill states descriptor cutoffs, QED and structural alerts are heuristics, not evidence of safety or efficacy
  • Standardizing or protonating structures for regulated or production pipelines without review: the bundled helpers do no tautomer, salt or pH handling by design
  • Simple workflows where the datamol wrapper library would be easier, as the skill itself recommends

Try asking

  • “Calculate MW, LogP, TPSA and Lipinski properties for the molecules in my molecules.smi file and export to CSV”
  • “Find all compounds in database.sdf that are similar to aspirin using Morgan fingerprints with a 0.7 threshold”
  • “Filter a library to keep only molecules containing a carboxylic acid substructure”
  • “Generate 3D conformers with ETKDG for this SMILES and minimize them with a force field”
Step-by-step guide: how to use RDKit Cheminformatics ToolkitInstall, first run, examples, tips and FAQs

Install in 3 steps

  1. 1

    Download the skill

    The ZIP contains the 11 original files, the MIT licence and an attribution note.

    rdkit.zip
  2. 2

    Add it to your agent

    Claude Code (all projects)

    mkdir -p ~/.claude/skills && unzip rdkit.zip -d ~/.claude/skills/

    Claude Code / Agent SDK (this project only)

    mkdir -p .claude/skills && unzip rdkit.zip -d .claude/skills/

    Claude apps (web/desktop): Settings → Capabilities → Skills → Upload skill, and choose the ZIP.

  3. 3

    Ask for the task

    No special command needed — the agent reads the skill's description and loads it when your request matches. Try one of the prompts above.

Get better results

  • Install rdkit in an isolated environment and avoid mixing conda and PyPI RDKit builds, as the skill warns
  • Validate outputs yourself: check invalid-record logs and do not treat similarity 1.0 as identity, since the search ignores chirality unless --chirality is set
  • Review the bundled scripts before running them on sensitive data, since they execute locally with your permissions

What's inside

  • references/api_reference.md
  • references/core_capabilities.md
  • references/descriptors_reference.md
  • references/review.md
  • references/smarts_patterns.md
  • references/workflows_and_best_practices.md
  • scripts/_common.py
  • scripts/molecular_properties.py
  • scripts/similarity_search.py
  • scripts/substructure_filter.py
  • SKILL.md

Redistributed unmodified from K-Dense-AI/scientific-agent-skills under the MIT licence. The assessment was drafted with AI from the skill's files on 2026-10-29. Skills can instruct your agent to run code — read SKILL.md and any scripts before installing.