cheminformatics-definitions

cheminformatics-definitions is a skill for Claude Code from synthetic-sciences/openscience. It costs 155 tokens per session (2,114 once invoked), scanned A, original, Apache-2.0.

A guide to choosing precise RDKit definitions before calculating molecular descriptors. RDKit is a cheminformatics toolkit, and molecular descriptors are numerical properties used to describe chemical structures.

In plain words
What is it for?
Use it when computing chemical properties such as Lipinski donor and acceptor counts, polar surface area, or QED scores. It helps align calculations with the convention required by the question.
Why use it?
Different valid definitions can produce different hydrogen-bond counts, surface areas, and molecular strings. Naming the definition makes results understandable and reproducible.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it when computing chemical properties such as Lipinski donor and acceptor counts, polar surface area, or QED scores. It helps align calculations with the convention required by the question.

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Install with agentmods
npx agentmods add skills/synthetic-sciences/openscience/cheminformatics-definitions
About the project

synthetic-sciences/openscience is an AI workbench that carries out scientific research by reading papers, forming hypotheses, writing and running code, conducting experiments, analyzing results, and preparing reports. Researchers use it for work in machine learning, biology, physics, and chemistry with remote or local models. Catalogue add-ons extend its scientific workflows through skills and instructions.

synthetic-sciences/openscience · 4,025 stars · on GitHub · openscience.sh

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.

Any agent
npx skills add synthetic-sciences/openscience --skill cheminformatics-definitions
Clone the repo
git clone --depth 1 https://github.com/synthetic-sciences/openscience

Made for: Claude Code.

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.

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README.md
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Per session 155 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,114 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00155 $0.02114
Opus 5.5 $0.00062 $0.00846
Sonnet 5.5 $0.00031 $0.00423
Haiku 4.5 $0.00015 $0.00211

Measured 1mo ago against content hash 195318cab291, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

cheminformatics-definitions 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 1mo ago.

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.

backend/cli/skills/chemistry/cheminformatics-definitions/SKILL.md · 116 lines

How it starts

The opening of the file, as written. The whole thing — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Cheminformatics definitions

The same molecule has several hydrogen-bond acceptor counts, several polar surface areas and several canonical SMILES, all correct under some definition. RDKit implements more than one of each. Compute with the definition the question uses, and print the definition next to the number; a bare "HBA = 7" is not reproducible.

Rules

  1. Lipinski counts. The original rule of five counts donors as the number of N-H and O-H bonds and acceptors as the number of N and O atoms. In RDKit these are rdMolDescriptors.CalcNumLipinskiHBD and CalcNumLipinskiHBA (also exposed as Lipinski.NHOHCount and Lipinski.NOCount). Lipinski.NumHDonors and Lipinski.NumHAcceptors (same as rdMolDescriptors.CalcNumHBD and CalcNumHBA) use SMARTS-based pharmacophore definitions that exclude, for example, amide nitrogens and include some sulfur; the two acceptor counts often differ by two or three. The rule's thresholds are MW <= 500, cLogP <= 5, HBD <= 5, HBA <= 10, with "at most one violation" in the original formulation. cLogP in RDKit is Wildman-Crippen (Crippen.MolLogP), which differs from XLogP3 or other predictors by up to a log unit; name the method.
  2. Molecular weight. Descriptors.MolWt is the average isotopic mass, Descriptors.ExactMolWt the monoisotopic mass; both depend on whether the counterion was stripped first.
  3. TPSA. Ertl's fragment method. RDKit's default (Descriptors.TPSA(mol) or rdMolDescriptors.CalcTPSA(mol)) sums N and O contributions only, matching the reference values in the original paper; includeSandP=True adds S and P. Sulfonamides and phosphates shift by roughly 10 square angstroms between the two.
  4. QED. QED.qed(mol) uses Bickerton's mean weights by default; QED.weights_max and QED.weights_none give different values, and QED.properties(mol) exposes the eight underlying components (which use RDKit's own HBA, HBD and alert definitions). Report "QED, RDKit, mean weights".
  5. Rotatable bonds. rdMolDescriptors.CalcNumRotatableBonds(mol, strict) has NumRotatableBondsOptions.NonStrict, Strict (excludes amide C-N and similar) and StrictLinkages; Veber-style filters were derived with a particular definition, so state which was used.
  6. InChI and InChIKey. Chem.MolToInchi(mol) with no options yields standard InChI (InChI=1S/); any option such as /FixedH yields a non-standard InChI (InChI=1/) whose key is not comparable to standard keys. Chem.MolToInchiKey(mol) gives the 27-character key: a 14-character skeleton block, an 8-character block for stereo and isotopes, a version and standard flag, then a protonation character. Stereoisomers share the first block, so matching on it is skeleton matching. Standard InChI normalizes mobile hydrogens, so some tautomers collapse to one key and others do not.
  7. SMILES. Chem.MolToSmiles(mol) is canonical and isomeric by default (isomericSmiles=True keeps stereo and isotopes; False drops them; kekuleSmiles=True after Chem.Kekulize writes explicit bond orders). Canonical means canonical within one toolkit and version; never join tables from different toolkits on SMILES text. Recanonicalize everything through the same RDKit build or join on InChIKey.
  8. Standardization order. rdMolStandardize.Cleanup (sanitize, disconnect metals, normalize functional groups, reionize), FragmentParent (largest organic fragment, which is the usual salt stripping), ChargeParent (uncharged fragment parent, or Uncharger().uncharge), TautomerEnumerator().Canonicalize (or TautomerParent). Chem.SaltRemover.SaltRemover strips a fixed list of counterions instead and behaves differently for solvates and mixed salts. Uncharging is not protonation at pH 7.4; a pKa-based protonation step is a different, separately named operation. Descriptors on the parent differ from descriptors on the drawn salt form; say which was profiled.
  9. Aromaticity. RDKit's default model differs from the MDL model (Chem.SetAromaticity(mol, Chem.AromaticityModel.AROMATICITY_MDL) after Chem.Kekulize(mol, clearAromaticFlags=True)) and from OpenBabel or Daylight perception. Aromatic ring counts, aromatic-atom fractions and lowercase SMARTS matches all change with the model. Inputs with unusual valences may need Chem.MolFromSmiles(smi, sanitize=False) followed by Chem.SanitizeMol with explicit flags; record any molecule that failed to parse rather than dropping it silently.
  10. Hydrogens and stereo. Descriptors that count hydrogens need the implicit-H graph, 3D work needs Chem.AddHs; write canonical SMILES after Chem.RemoveHs. Chem.FindMolChiralCenters(mol, includeUnassigned=True, useLegacyImplementation=False) reveals unspecified centers that will make "same molecule" comparisons ambiguous.
  11. Always state rdkit.__version__, the function and arguments, the standardization steps and their order, and whether values are for the parent or the drawn form. Put a definitions footnote under every property table.

Read the full file on GitHub · 116 lines

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. 1mo ago First seen · 116 lines · 155 tokens per session scan A 195318cab291

Subscribe to this mod's changes

cheminformatics-definitions is a skill published in the GitHub repository synthetic-sciences/openscience (4,025 stars, last pushed today), licensed Apache-2.0. It adds 155 tokens to every session and 2,114 once invoked, about $0.0006 per session on Opus 5.5. 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 2026-09-15.