ToolUniverse is a collection of tools, interfaces, and supporting components for building AI systems that perform scientific work. It is for developers creating AI scientist agents that use APIs, databases, machine-learning tools, and domain-specific utilities. The catalogue includes skills, commands, an MCP server, an agent, and a hook for working with the ecosystem.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mims-harvard/ToolUniverse --skill tooluniverse-cancer-classificationgit clone --depth 1 https://github.com/mims-harvard/ToolUniverseWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mims-harvard/tooluniverse/tooluniverse-cancer-classification)<a href="https://agentmods.dev/skills/mims-harvard/tooluniverse/tooluniverse-cancer-classification"><img src="https://agentmods.dev/badge/skills/mims-harvard/tooluniverse/tooluniverse-cancer-classification/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mims-harvard/tooluniverse/tooluniverse-cancer-classification"><img src="https://agentmods.dev/badge/skills/mims-harvard/tooluniverse/tooluniverse-cancer-classification.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00080 | $0.02903 |
| Opus 5 | $0.00040 | $0.01452 |
| Sonnet 5 | $0.00016 | $0.00581 |
| Haiku 4.5 | $0.00008 | $0.00290 |
Grade A, and why
tooluniverse-cancer-classification scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cancer Classification via OncoTree
Standardize cancer type nomenclature using the OncoTree ontology. Resolves free-text tumor descriptions to structured codes with UMLS/NCI cross-references, enabling downstream use in OncoKB variant annotation and GDC cohort selection.
When to Use
Apply when researcher asks about:
- "What is the OncoTree code for [tumor description]?"
- "Find all subtypes of [cancer type]"
- "What cancers originate in [tissue]?"
- "I need the tumor type code for OncoKB annotation"
- "What is the TCGA/COSMIC code for [cancer]?"
- "List all CNS/Brain cancer subtypes"
- "What NCI code corresponds to glioblastoma?"
Key Tools
| Tool | Purpose | Key Params |
|---|---|---|
OncoTree_search |
Free-text search for cancer types | query (tumor name or description) |
OncoTree_get_type |
Full details for a known OncoTree code | code (e.g., "LUAD", "AML") |
OncoTree_list_tissues |
List all 32 tissue categories | (no params) |
OncoKB_annotate_variant |
Variant annotation using OncoTree code | gene, variant, tumor_type |
GDC_get_mutation_frequency |
Pan-cancer mutation frequency (TCGA) | gene_symbol |
Workflow
Phase 1: Cancer Type Discovery
Start with free-text search to find matching OncoTree codes:
OncoTree_search(query="breast cancer")
-> Returns list: code, name, main_type, tissue, parent, level, external_references
Key response fields:
code: OncoTree code (e.g., "BRCA", "IBC") — use this in OncoKB callslevel: hierarchy depth (1=tissue, 2=main type, 3-5=subtypes)parent: parent node code for navigating the hierarchyexternal_references.UMLS: UMLS CUI listexternal_references.NCI: NCI thesaurus code list
Search tips:
- Broad terms ("lung cancer") return many results; narrow by tissue or level
- Use tissue-specific terms ("invasive breast carcinoma") for precise matching
- Acronyms work: query="GBM" finds glioblastoma, query="AML" finds leukemia types
Phase 2: Code Validation and Detail Retrieval
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 205 lines · 80 tokens per session scan A 4de3ed2cfa17
tooluniverse-cancer-classification is a skill published in the GitHub repository mims-harvard/ToolUniverse (1,680 stars, last pushed 2d ago), licensed Apache-2.0. It adds 80 tokens to every session and 2,903 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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