drug-discovery-prompts/upstream/mims-harvard-ToolUniverse/skills/tooluniverse-cs-setup/templates/router_SKILL.md

lineage_type, upstream_source, upstream_sha, imported_at, prompt_class, upstream_changes, name, description

lineage_type	upstream_source	upstream_sha	imported_at	prompt_class	upstream_changes	name	description
import	https://github.com/mims-harvard/ToolUniverse/blob/bb632a34/skills/tooluniverse-cs-setup/templates/router_SKILL.md	bb632a34	2026-07-01	prompt	accepted	tooluniverse-research	Biomedical and scientific research via ToolUniverse's 2500+ tools across 133 structured workflows — drug research, disease research, gene and variant interpretation, cancer genomics, clinical trials, ADMET prediction, pharmacovigilance and adverse events, CRISPR screens, protein and structure analysis, epidemiology, and graded literature reviews. Use for "tell me about drug/gene/disease/variant X", multi-database investigations, cross-validating biomedical claims, ID translation, or any structured scientific lookup spanning FDA, ChEMBL, PubChem, ClinicalTrials.gov, UniProt, Ensembl, PubMed, and 200+ other databases.

ToolUniverse Research

Brings ToolUniverse's 2500+ scientific tools and 133 structured research workflows into Claude Science. The tooluniverse PyPI package supplies the tools; this skill bundles the workflows and a kernel sidecar that wires them up.

Setup

Run all cells in the tooluniverse conda environment. Loading this skill auto-defines these helpers in the kernel:

• get_tu() → a loaded ToolUniverse instance (cache redirected to the workspace, since ~/.tooluniverse is read-only here).
• tu_workflows() → list all 133 workflows (name + description).
• find_tu_workflow(query) → rank workflows by relevance to a question.
• tu_workflow(name) → the full step-by-step procedure for one workflow.
• tu_tool_info(tu, name) → a tool's JSON spec, including its argument schema.

Answering a research question

1. Route to a workflow: find_tu_workflow("tell me about metformin") returns ranked names. (Or browse tu_workflows().)
2. Load its procedure: print(tu_workflow("tooluniverse-drug-research")) and follow the steps.
3. Execute the tools the workflow names. Every ToolName(args) reference maps to:

   tu = get_tu()
   tu.run({"name": "PubChem_get_CID_by_compound_name",
           "arguments": {"name": "metformin"}})
   

4. Confirm argument names before a call if unsure — tu_tool_info(tu, "PubChem_get_CID_by_compound_name") shows the exact schema. Workflow prose abbreviates arguments; the schema is authoritative.
5. Discover tools at runtime when no workflow fits:

   tu.run({"name": "Tool_Finder_Keyword",
           "arguments": {"description": "drug adverse events", "limit": 10}})
   

Notes

• Most tools work without API keys. A few (NCBI, OncoKB, NVIDIA, …) unlock enhanced access when keys are set in the env — add under Customize → Credentials, then expose them in the tooluniverse env.
• Workflows are self-contained: report templates, checklists, and tool references are appended to each as appendices.
• These workflows emphasize looking things up over recalling them — when a workflow says query a database, run the tool rather than answering from memory.