TO

tooluniverse-chemical-compound-retrieval

Retrieves and validates chemical compound data from PubChem and ChEMBL. It handles disambiguation and structure parsing to provide accurate molecular profiles.

Install

mkdir -p .claude/skills/tooluniverse-chemical-compound-retrieval && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/3545" && unzip -o skill.zip -d .claude/skills/tooluniverse-chemical-compound-retrieval && rm skill.zip

Installs to .claude/skills/tooluniverse-chemical-compound-retrieval

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Retrieve chemical compound data from PubChem and ChEMBL with disambiguation, cross-referencing, and stereochemistry handling. Use for resolving compound names to SMILES/InChI/CID/ChEMBL IDs (including OPSIN deterministic IUPAC-name-to-structure parsing), fetching molecular properties, distinguishing isomers/stereo forms, and cross-validating identity across databases. Always use English compound names; flags ambiguous queries (e.g., Vitamin D has multiple forms).
467 chars✓ has a “when” triggerlonger than Claude Code's old 250-char listing cap (fine on current versions)
Advanced

Key capabilities

  • Resolve compound names to CIDs and ChEMBL IDs
  • Parse systematic IUPAC names to structures
  • Fetch molecular properties and bioactivity data
  • Cross-validate identity across databases
  • Handle stereochemistry and isomer forms

How it works

It uses a multi-phase workflow to disambiguate names, resolve them to unique identifiers via PubChem/ChEMBL, and aggregate properties and bioactivity data.

Inputs & outputs

You give it
Compound name or chemical identifier
You get back
Compound profile with identifiers and properties

When to use tooluniverse-chemical-compound-retrieval

  • Convert IUPAC names to SMILES structures
  • Validate chemical compound identity across databases
  • Fetch molecular properties for specific CIDs
  • Disambiguate ambiguous chemical names

About this skill

Chemical Compound Information Retrieval

Retrieve comprehensive chemical compound data with proper disambiguation and cross-database validation.

LOOK UP DON'T GUESS: Never assume a CID, ChEMBL ID, or molecular property value. Always retrieve from PubChem/ChEMBL.

English-first: Always use English compound names in tool calls. Respond in user's language.

Domain Reasoning: Disambiguation

"Aspirin" = one compound. "Vitamin D" = multiple forms (D2/D3/active metabolite). For generic class names (steroids, vitamins, acids), present candidates and confirm before proceeding.


Workflow

Phase 0: Clarify (only if highly ambiguous -- skip for unambiguous names or specific IDs)
Phase 1: Disambiguate → resolve PubChem CID + ChEMBL ID
Phase 2: Retrieve data (silent)
Phase 3: Report compound profile

Phase 1: Disambiguation

# By name
result = tu.tools.PubChem_get_CID_by_compound_name(compound_name=name)
# By SYSTEMATIC (IUPAC) name -> structure, deterministic parser (no DB lookup)
opsin = tu.tools.OPSIN_name_to_structure(name="2-acetoxybenzoic acid")
# Returns {parsed, smiles, inchi, inchikey}; use the SMILES/InChIKey to anchor a
# PubChem_get_CID_by_SMILES lookup. Trade/trivial names give parsed=false -> fall
# back to PubChem_get_CID_by_compound_name for those.
# By SMILES
result = tu.tools.PubChem_get_CID_by_SMILES(smiles=smiles)
# Cross-reference
chembl_result = tu.tools.ChEMBL_search_molecules(query=name, limit=5)

Verify: CID + ChEMBL ID + canonical SMILES + stereochemistry + salt forms.

Phase 2: Data Retrieval

PubChem: PubChem_get_compound_properties_by_CID, PubChemBioAssay_get_assay_summary, PubChemTox_get_acute_effects, PubChem_get_compound_2D_image_by_CID

ChEMBL: ChEMBL_get_compound_record_activities, ChEMBL_get_molecule_targets, ChEMBL_get_assay_activities

Optional: PubChem_get_associated_patents_by_CID, PubChem_search_compounds_by_similarity

Phase 3: Report

Compound Profile with: Identity (CID, ChEMBL ID, IUPAC, SMILES), Chemical Properties (MW, LogP, HBD, HBA, PSA, Lipinski), Bioactivity (targets, IC50/Ki), Drug Info (if approved), Data Sources.


Fallback Chains

PrimaryFallback
PubChem name lookup (systematic name)OPSIN_name_to_structure → SMILES/InChIKey → PubChem_get_CID_by_SMILES
PubChem name lookupChEMBL search → SMILES → PubChem_get_CID_by_SMILES
ChEMBL bioactivityPubChem bioassay summary
Drug labelNote "unavailable"

Evidence Grading

GradeCriteria
ConfirmedCID + ChEMBL cross-match, InChI/SMILES agree
ProbableCID found, partial ChEMBL match
UncertainSingle database only, or multiple CIDs
UnverifiedNo cross-reference, single-source

Bioactivity: ChEMBL > PubChem BioAssay for curated data. IC50/Ki < 100nM = potent, 100nM-1uM = moderate, >10uM = weak. Lipinski violations reduce oral bioavailability but don't disqualify.


SMILES Verification

Always verify novel SMILES: python3 src/tooluniverse/tools/smiles_verifier.py --smiles "SMILES_STRING". Invalid SMILES produce wrong results or cryptic errors.


Tool Reference

PubChem: PubChem_get_CID_by_compound_name, PubChem_get_CID_by_SMILES, PubChem_get_compound_properties_by_CID, PubChem_get_compound_2D_image_by_CID, PubChemBioAssay_get_assay_summary, PubChemTox_get_acute_effects, PubChem_get_associated_patents_by_CID, PubChem_search_compounds_by_similarity, PubChem_search_compounds_by_substructure

ChEMBL: ChEMBL_search_drugs, ChEMBL_get_molecule, ChEMBL_get_activity, ChEMBL_get_target, ChEMBL_search_targets, ChEMBL_search_assays

Name parsing: OPSIN_name_to_structure (param name) — deterministic IUPAC/systematic-name → SMILES/InChI/InChIKey parser; the go-to for resolving a systematic name to structure without a DB round-trip. Trade/trivial names return parsed=false (use PubChem name lookup for those).

When not to use it

  • Retrieving non-chemical data
  • Guessing identifiers without database lookup

Prerequisites

Access to PubChem and ChEMBL APIs

Limitations

  • Requires English compound names
  • Ambiguous names require user confirmation

How it compares

It enforces a strict 'look up don't guess' policy with cross-database validation instead of relying on single-source lookups.

Compared to similar skills

tooluniverse-chemical-compound-retrieval side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
tooluniverse-chemical-compound-retrieval (this skill)12moNo flagsAdvanced
literature-review5592moReviewAdvanced
openalex-database487moReviewIntermediate
market-research-reports387moReviewAdvanced

Try saying

Example prompts that trigger this skill in your AI assistant.

More by mims-harvard

View all by mims-harvard

tooluniverse-drug-research

mims-harvard

Generates comprehensive drug research reports with compound disambiguation, evidence grading, and mandatory completeness sections. Covers identity, chemistry, pharmacology, targets, clinical trials, safety, pharmacogenomics, and ADMET properties. Use when users ask about drugs, medications, therapeutics, or need drug profiling, safety assessment, or clinical development research.

323

tooluniverse-pharmacovigilance

mims-harvard

Analyze drug safety signals from FDA adverse event reports, label warnings, and pharmacogenomic data. Calculates disproportionality measures (PRR, ROR), identifies serious adverse events, assesses pharmacogenomic risk variants. Use when asked about drug safety, adverse events, post-market surveillance, or risk-benefit assessment.

323

tooluniverse-precision-oncology

mims-harvard

Provide actionable treatment recommendations for cancer patients based on molecular profile. Interprets tumor mutations, identifies FDA-approved therapies, finds resistance mechanisms, matches clinical trials. Use when oncologist asks about treatment options for specific mutations (EGFR, KRAS, BRAF, etc.), therapy resistance, or clinical trial eligibility.

321

tooluniverse-expression-data-retrieval

mims-harvard

Retrieves gene expression and omics datasets from ArrayExpress and BioStudies with gene disambiguation, experiment quality assessment, and structured reports. Creates comprehensive dataset profiles with metadata, sample information, and download links. Use when users need expression data, omics datasets, or mention ArrayExpress (E-MTAB, E-GEOD) or BioStudies (S-BSST) accessions.

217

tooluniverse-literature-deep-research

mims-harvard

Conduct comprehensive literature research with target disambiguation, evidence grading, and structured theme extraction. Creates a detailed report with mandatory completeness checklist, biological model synthesis, and testable hypotheses. For biological targets, resolves official IDs (Ensembl/UniProt), synonyms, naming collisions, and gathers expression/pathway context before literature search. Default deliverable is a report file; for single factoid questions, uses a fast verification mode and may include an inline answer. Use when users need thorough literature reviews, target profiles, or to verify specific claims from the literature.

213

tooluniverse-target-research

mims-harvard

Gather comprehensive biological target intelligence from 9 parallel research paths covering protein info, structure, interactions, pathways, expression, variants, drug interactions, and literature. Features collision-aware searches, evidence grading (T1-T4), explicit Open Targets coverage, and mandatory completeness auditing. Use when users ask about drug targets, proteins, genes, or need target validation, druggability assessment, or comprehensive target profiling.

25

You might also like

literature-review

K-Dense-AI

Conduct comprehensive, systematic literature reviews using multiple academic databases (PubMed, arXiv, bioRxiv, Semantic Scholar, etc.). This skill should be used when conducting systematic literature reviews, meta-analyses, research synthesis, or comprehensive literature searches across biomedical, scientific, and technical domains. Creates professionally formatted markdown documents and PDFs with verified citations in multiple citation styles (APA, Nature, Vancouver, etc.).

5591,298

openalex-database

davila7

Query and analyze scholarly literature using the OpenAlex database. This skill should be used when searching for academic papers, analyzing research trends, finding works by authors or institutions, tracking citations, discovering open access publications, or conducting bibliometric analysis across 240M+ scholarly works. Use for literature searches, research output analysis, citation analysis, and academic database queries.

48202

market-research-reports

davila7

Generate comprehensive market research reports (50+ pages) in the style of top consulting firms (McKinsey, BCG, Gartner). Features professional LaTeX formatting, extensive visual generation with scientific-schematics and generate-image, deep integration with research-lookup for data gathering, and multi-framework strategic analysis including Porter's Five Forces, PESTLE, SWOT, TAM/SAM/SOM, and BCG Matrix.

38162

scientific-brainstorming

davila7

Research ideation partner. Generate hypotheses, explore interdisciplinary connections, challenge assumptions, develop methodologies, identify research gaps, for creative scientific problem-solving.

37155

exa-search

benjaminjackson

Search the web for content matching a query with AI-powered semantic search. Use for finding relevant web pages, research papers, news articles, code repositories, or any web content by meaning rather than just keywords.

9106

scientific-critical-thinking

davila7

Evaluate research rigor. Assess methodology, experimental design, statistical validity, biases, confounding, evidence quality (GRADE, Cochrane ROB), for critical analysis of scientific claims.

1888

Search skills

Search the agent skills registry