Tooluniverse Target Research
This is a comprehensive drug target intelligence gathering workflow that pulls data from nine parallel research paths including tissue expression (GTEx, HPA), protein interactions (STRING), genetic variants (ClinVar, gnomAD), and druggability databases (DGIdb, ChEMBL). It's built for answering "tell me everything about target X" queries in drug discovery, with mandatory evidence grading (T1-T4), inline citations, and a report-first approach that creates a structured markdown file before populating it progressively. The workflow includes a target evaluation framework that walks through genetic evidence, druggability, safety, and competitive landscape. The instructions are extremely prescriptive about avoiding hallucinations (look up, don't guess) and handling tool parameter verification before making calls. Worth noting it explicitly documents negative results rather than leaving empty sections, which is good practice for research transparency.
- skills.sh installs
- 412
- GitHub stars
- 1.8K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add mims-harvard/tooluniverse --skill tooluniverse-target-research --agent claude-codeInstalls into .claude/skills of the current project.
Files
Comprehensive Target Intelligence Gatherer
Gather complete target intelligence by exploring 9 parallel research paths. Supports targets identified by gene symbol, UniProt accession, Ensembl ID, or gene name.
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- Repository
- github.com/mims-harvard/tooluniverse
- Categories
- Data Science & ML, Automation & Workflows, Sales & Marketing
- First seen
- Jun 3, 2026
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