drug-discovery-prompts/upstream/mims-harvard-ToolUniverse/catalogue/skills

title, task, lineage_type, upstream_source, upstream_sha, imported_at, prompt_class, upstream_changes, author, validated

title	task	lineage_type	upstream_source	upstream_sha	imported_at	prompt_class	upstream_changes	author	validated
ToolUniverse Skills		import	https://github.com/mims-harvard/ToolUniverse/blob/bb632a34/skills/README.md	bb632a34	2026-07-01	catalogue	accepted	upstream	false

ToolUniverse Skills

68 pre-built research skills for AI agents. Skills are automatically available — just ask naturally.

"Find the E. coli K-12 genome"           → tooluniverse-sequence-retrieval
"What do we know about Alzheimer's?"      → tooluniverse-disease-research
"Assess EGFR as a drug target"            → tooluniverse-target-research
"Run differential expression on my data"  → tooluniverse-rnaseq-deseq2

Install

npx skills add mims-harvard/ToolUniverse

All Skills

Research Skills

Skill	Description
tooluniverse	Router — dispatches to the right specialized skill automatically
tooluniverse-adverse-event-detection	Adverse drug event signal detection using FDA FAERS data
tooluniverse-antibody-engineering	Antibody humanization, affinity maturation, and optimization
tooluniverse-binder-discovery	Small molecule binder discovery (structure-based and ligand-based)
tooluniverse-cancer-variant-interpretation	Clinical interpretation of somatic cancer mutations
tooluniverse-chemical-compound-retrieval	Chemical compound info from PubChem and ChEMBL
tooluniverse-chemical-safety	Chemical safety and toxicology assessment (ADMET-AI, CTD, FDA)
tooluniverse-clinical-guidelines	Clinical practice guidelines from 12+ sources (NICE, WHO, ADA, etc.)
tooluniverse-clinical-trial-design	Clinical trial design feasibility assessment
tooluniverse-clinical-trial-matching	Patient-to-trial matching for precision medicine
tooluniverse-crispr-screen-analysis	CRISPR knockout/activation screen analysis
tooluniverse-custom-tool	Create and register custom tools
tooluniverse-disease-research	Comprehensive disease reports using 100+ tools
tooluniverse-drug-drug-interaction	Drug-drug interaction prediction and risk assessment
tooluniverse-drug-repurposing	Drug repurposing via target-, compound-, and disease-driven strategies
tooluniverse-drug-research	Comprehensive drug reports with evidence grading
tooluniverse-drug-target-validation	Computational drug target validation (10 dimensions)
tooluniverse-epigenomics	Epigenomics and gene regulation (ENCODE, JASPAR, methylation)
tooluniverse-expression-data-retrieval	Gene expression datasets from ArrayExpress and BioStudies
tooluniverse-gene-enrichment	Gene enrichment and pathway analysis (gseapy, PANTHER, STRING, etc.)
tooluniverse-gwas-drug-discovery	GWAS signals to drug targets and repurposing opportunities
tooluniverse-gwas-finemapping	Causal variant prioritization via statistical fine-mapping
tooluniverse-gwas-snp-interpretation	Genetic variant interpretation from GWAS studies
tooluniverse-gwas-study-explorer	GWAS study comparison and meta-analysis
tooluniverse-gwas-trait-to-gene	Gene-trait associations from GWAS Catalog and Open Targets
tooluniverse-image-analysis	Microscopy image analysis and quantitative imaging
tooluniverse-immune-repertoire-analysis	TCR/BCR immune repertoire analysis
tooluniverse-immunotherapy-response-prediction	Predict response to immune checkpoint inhibitors
tooluniverse-infectious-disease	Pathogen characterization and drug repurposing for outbreaks
tooluniverse-install-skills	Auto-detect and install missing skills
tooluniverse-literature-deep-research	Literature research with evidence grading and theme extraction
tooluniverse-metabolomics	Metabolomics research (metabolite ID, study analysis)
tooluniverse-metabolomics-analysis	Metabolomics data analysis (quantification, pathway, flux)
tooluniverse-multi-omics-integration	Multi-omics dataset integration
tooluniverse-multiomic-disease-characterization	Multi-omics disease characterization
tooluniverse-network-pharmacology	Compound-target-disease network analysis
tooluniverse-pharmacovigilance	Drug safety signal analysis from FDA reports
tooluniverse-phylogenetics	Phylogenetics and sequence analysis
tooluniverse-polygenic-risk-score	Polygenic risk score construction and interpretation
tooluniverse-precision-medicine-stratification	Patient stratification for precision medicine
tooluniverse-precision-oncology	Actionable cancer treatment recommendations from molecular profiles
tooluniverse-protein-interactions	Protein-protein interaction networks (STRING, BioGRID)
tooluniverse-protein-structure-retrieval	Protein structures from PDB, PDBe, and AlphaFold
tooluniverse-protein-therapeutic-design	AI-guided protein therapeutic design (RFdiffusion, etc.)
tooluniverse-proteomics-analysis	Mass spectrometry proteomics analysis
tooluniverse-rare-disease-diagnosis	Rare disease differential diagnosis from phenotype and genetics
tooluniverse-rnaseq-deseq2	RNA-seq differential expression with PyDESeq2
tooluniverse-sdk	Build AI scientist systems using the Python SDK
tooluniverse-sequence-retrieval	DNA, RNA, and protein sequences from NCBI and ENA
tooluniverse-single-cell	Single-cell RNA-seq analysis (scanpy, anndata)
tooluniverse-spatial-omics-analysis	Spatial multi-omics data integration
tooluniverse-spatial-transcriptomics	Spatial transcriptomics (10x Visium, MERFISH, seqFISH)
tooluniverse-statistical-modeling	Statistical modeling and regression for biomedical data
tooluniverse-structural-variant-analysis	Structural variant analysis for clinical genomics
tooluniverse-systems-biology	Pathway analysis (Reactome, KEGG, WikiPathways)
tooluniverse-target-research	Comprehensive drug target profiling (9 research paths)
tooluniverse-variant-analysis	VCF processing, variant annotation, and SV/CNV interpretation
tooluniverse-variant-interpretation	Clinical variant interpretation with ACMG classification

Developer Skills

Skill	Description
setup-tooluniverse	Install and configure ToolUniverse (MCP, CLI, or SDK)
tooluniverse-cs-setup	Install/update ToolUniverse in Claude Science (conda env + pip package + native skill; not MCP)
create-tooluniverse-skill	Create new skills with test-driven methodology
devtu-auto-discover-apis	Discover life science APIs and create tools automatically
devtu-create-tool	Create new scientific tools with proper structure and testing
devtu-docs-quality	Documentation quality validation and auditing
devtu-fix-tool	Diagnose and fix failing tools
devtu-github	GitHub workflow (push, pre-commit hooks, tests)
devtu-optimize-descriptions	Optimize tool descriptions for clarity
devtu-optimize-skills	Improve skill quality (evidence grading, disambiguation)
devtu-self-evolve	Full self-improvement cycle (discover, create, test, fix)

Skill Structure

skill-name/
├── SKILL.md          # Main instructions (<500 lines)
├── QUICK_START.md    # Quick reference (optional)
├── EXAMPLES.md       # Usage examples (optional)
└── references/       # Detailed reference material (optional)

Contributing

1. Create skill-name/SKILL.md with proper frontmatter
2. Keep SKILL.md concise (<500 lines)
3. Add examples for common use cases
4. See create-tooluniverse-skill for the full workflow