rdkit

rdkit is a skill for Claude Code, Codex from benchflow-ai/skillsbench. It costs 80 tokens per session (5,407 once invoked), scanned A, original, Apache-2.0.

A Python toolkit for cheminformatics, the use of software to represent and study chemical molecules. It works with formats such as SMILES and SDF and supports molecular properties, fingerprints, structure searches, reactions, and 2D or 3D models.

In plain words
What is it for?
It is for drug-discovery and chemistry work such as reading and writing structures, calculating descriptors, finding substructures, comparing molecules, generating coordinates, and drawing them.
Why use it?
It provides detailed control for analysing molecules and chemical reactions without implementing molecular data handling from scratch.

Skill for Claude CodeCodex

About the project

SkillsBench is a benchmark for measuring how effectively AI agents use modular skills—folders containing instructions, scripts, and resources—to complete specialized tasks. It helps researchers and developers evaluate both skill quality and agent behavior, including tasks that require combining multiple skills. The catalogue’s skills and instructions are evaluated as part of this workflow.

benchflow-ai/skillsbench · 1,747 stars · on GitHub

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/benchflow-ai/skillsbench/rdkit
Any agent
npx skills add benchflow-ai/skillsbench --skill rdkit
Clone the repo
git clone --depth 1 https://github.com/benchflow-ai/skillsbench

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for rdkit

README.md
[![agentmods](https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/rdkit.svg)](https://agentmods.dev/skills/benchflow-ai/skillsbench/rdkit)
Your own site
<a href="https://agentmods.dev/skills/benchflow-ai/skillsbench/rdkit"><img src="https://agentmods.dev/badge/skills/benchflow-ai/skillsbench/rdkit.svg" alt="Measured on agentmods" height="20"></a>
Per session 80 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 5,407 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00080 $0.05407
Opus 5 $0.00040 $0.02704
Sonnet 5 $0.00016 $0.01081
Haiku 4.5 $0.00008 $0.00541

Measured 5d ago against content hash 765c294784d9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

rdkit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/molecular_properties.py, scripts/similarity_search.py, scripts/substructure_filter.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

4 near-identical copies found in the catalogue:

  • rdkit — 100% identical, 1 lines differ
  • rdkit — 100% identical, 1 lines differ
  • rdkit — 100% identical, 0 lines differ
  • rdkit — 100% identical, 34 lines differ
tasks-extra/find-topk-similiar-chemicals/environment/skills/rdkit/SKILL.md · 770 lines

How it starts

The opening of the file, as written. The whole thing — 770 lines — stays where its author put it; the contents beside it link to each section on GitHub.

RDKit Cheminformatics Toolkit

Overview

RDKit is a comprehensive cheminformatics library providing Python APIs for molecular analysis and manipulation. This skill provides guidance for reading/writing molecular structures, calculating descriptors, fingerprinting, substructure searching, chemical reactions, 2D/3D coordinate generation, and molecular visualization. Use this skill for drug discovery, computational chemistry, and cheminformatics research tasks.

Core Capabilities

1. Molecular I/O and Creation

Reading Molecules:

Read molecular structures from various formats:

from rdkit import Chem

# From SMILES strings
mol = Chem.MolFromSmiles('Cc1ccccc1')  # Returns Mol object or None

# From MOL files
mol = Chem.MolFromMolFile('path/to/file.mol')

# From MOL blocks (string data)
mol = Chem.MolFromMolBlock(mol_block_string)

# From InChI
mol = Chem.MolFromInchi('InChI=1S/C6H6/c1-2-4-6-5-3-1/h1-6H')

Writing Molecules:

Convert molecules to text representations:

# To canonical SMILES
smiles = Chem.MolToSmiles(mol)

# To MOL block
mol_block = Chem.MolToMolBlock(mol)

# To InChI
inchi = Chem.MolToInchi(mol)

Batch Processing:

For processing multiple molecules, use Supplier/Writer objects:

# Read SDF files
suppl = Chem.SDMolSupplier('molecules.sdf')
for mol in suppl:
    if mol is not None:  # Check for parsing errors
        # Process molecule
        pass

# Read SMILES files
suppl = Chem.SmilesMolSupplier('molecules.smi', titleLine=False)

# For large files or compressed data
with gzip.open('molecules.sdf.gz') as f:
    suppl = Chem.ForwardSDMolSupplier(f)
    for mol in suppl:
        # Process molecule
        pass

# Multithreaded processing for large datasets
suppl = Chem.MultithreadedSDMolSupplier('molecules.sdf')

# Write molecules to SDF
writer = Chem.SDWriter('output.sdf')
for mol in molecules:
    writer.write(mol)
writer.close()

Important Notes:

  • All MolFrom* functions return None on failure with error messages
  • Always check for None before processing molecules
  • Molecules are automatically sanitized on import (validates valence, perceives aromaticity)

Read the full file on GitHub · 770 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 5d ago First seen · 770 lines · 80 tokens per session scan A 765c294784d9

Subscribe to this mod's changes

rdkit is a skill published in the GitHub repository benchflow-ai/skillsbench (1,747 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 80 tokens to every session and 5,407 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.