Retrieve comprehensive chemical compound data with proper disambiguation and cross-database validation.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiontooluniverse-chemical-compound-retrievalExecute the skills CLI command in your project's root directory to begin installation:
Fetches tooluniverse-chemical-compound-retrieval from mims-harvard/tooluniverse and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate tooluniverse-chemical-compound-retrieval. Access via /tooluniverse-chemical-compound-retrieval in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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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.
"Aspirin" = one compound. "Vitamin D" = multiple forms (D2/D3/active metabolite). For generic class names (steroids, vitamins, acids), present candidates and confirm before proceeding.
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
# By name
result = tu.tools.PubChem_get_CID_by_compound_name(compound_name=name)
# By SMILES
result = tu.tools.PubChem_get_CID_by_SMILES(smiles=smiles)
# Cross-reference
chembl_result = tu.tools.ChEMBL_search_compounds(query=name, limit=5)
Verify: CID + ChEMBL ID + canonical SMILES + stereochemistry + salt forms.
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_bioactivity_by_chemblid, ChEMBL_get_target_by_chemblid, ChEMBL_get_assays_by_chemblid
Optional: PubChem_get_associated_patents_by_CID, PubChem_search_compounds_by_similarity
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.
| Primary | Fallback |
|---|---|
| PubChem name lookup | ChEMBL search → SMILES → PubChem_get_CID_by_SMILES |
| ChEMBL bioactivity | PubChem bioassay summary |
| Drug label | Note "unavailable" |
| Grade | Criteria |
|---|---|
| Confirmed | CID + ChEMBL cross-match, InChI/SMILES agree |
| Probable | CID found, partial ChEMBL match |
| Uncertain | Single database only, or multiple CIDs |
| Unverified | No 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.
Always verify novel SMILES: python3 src/tooluniverse/tools/smiles_verifier.py --smiles "SMILES_STRING". Invalid SMILES produce wrong results or cryptic errors.
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
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
We added tooluniverse-chemical-compound-retrieval from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
tooluniverse-chemical-compound-retrieval is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: tooluniverse-chemical-compound-retrieval is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend tooluniverse-chemical-compound-retrieval for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Useful defaults in tooluniverse-chemical-compound-retrieval — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for tooluniverse-chemical-compound-retrieval matched our evaluation — installs cleanly and behaves as described in the markdown.
tooluniverse-chemical-compound-retrieval reduced setup friction for our internal harness; good balance of opinion and flexibility.
tooluniverse-chemical-compound-retrieval has been reliable in day-to-day use. Documentation quality is above average for community skills.
tooluniverse-chemical-compound-retrieval reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added tooluniverse-chemical-compound-retrieval from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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