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-cell-line-profilinggit 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-cell-line-profiling)<a href="https://agentmods.dev/skills/mims-harvard/tooluniverse/tooluniverse-cell-line-profiling"><img src="https://agentmods.dev/badge/skills/mims-harvard/tooluniverse/tooluniverse-cell-line-profiling/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-cell-line-profiling"><img src="https://agentmods.dev/badge/skills/mims-harvard/tooluniverse/tooluniverse-cell-line-profiling.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 | $0.00100 | $0.05011 |
| Opus 5 | $0.00050 | $0.02506 |
| Sonnet 5 | $0.00020 | $0.01002 |
| Haiku 4.5 | $0.00010 | $0.00501 |
Grade A, and why
tooluniverse-cell-line-profiling 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 6d 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 — 276 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cancer Cell Line Profiling and Selection
Comprehensive profiling of cancer cell lines for experimental model selection. Transforms a query (cancer type, gene, or cell line name) into an actionable report covering identity verification, molecular features, gene dependencies, drug sensitivities, and druggable targets.
KEY PRINCIPLES:
- Decision-first - Answer "which cell line should I use?" not "here is all the data"
- Multi-source validation - Cross-reference DepMap, Cellosaurus, COSMIC, PharmacoDB
- Actionable output - Ranked cell line recommendations with rationale
- Practical focus - Include availability, growth characteristics, common pitfalls
- Gene-aware - When a gene of interest is given, prioritize lines with relevant mutations/dependencies
- Source-referenced - Cite database sources for every claim
- English-first queries - Always use English terms in tool calls, even if the user writes in another language
LOOK UP, DON'T GUESS
When uncertain about any scientific fact, SEARCH databases first rather than reasoning from memory. A database-verified answer is always more reliable than a guess.
COMPUTE, DON'T DESCRIBE
When analysis requires computation (statistics, data processing, scoring, enrichment), write and run Python code via Bash. Don't describe what you would do — execute it and report actual results. Use ToolUniverse tools to retrieve data, then Python (pandas, scipy, statsmodels, matplotlib) to analyze it.
When to Use
Apply for: cell line selection by cancer type/gene, cell line profiling, gene dependencies, drug sensitivity queries, cell line comparisons, mutation checks.
Phase 0: Tool Parameter Reference (CRITICAL)
BEFORE calling ANY tool, verify parameters against this table.
| Tool | Key Parameters | Notes |
|---|---|---|
DepMap_search_cell_lines |
query (required) |
Search by name, e.g., "A549", "MCF" |
DepMap_get_cell_line |
model_name OR model_id |
Name: "A549"; ID: "SIDM00001" |
DepMap_get_cell_lines |
tissue, cancer_type, page_size |
Filter by tissue (e.g., "Lung") |
DepMap_get_gene_dependencies |
gene_symbol (required), model_id |
Gene effect scores; negative = essential |
DepMap_search_genes |
query (required) |
Validate gene symbol in DepMap first |
cellosaurus_search_cell_lines |
q (required), size |
Solr syntax: id:HeLa, ox:9606 AND char:cancer |
cellosaurus_get_cell_line_info |
accession (required, CVCL_ format) |
Full cell line record |
cellosaurus_query_converter |
query (required) |
Natural language to Solr syntax |
COSMIC_search_mutations |
terms OR query, max_results |
Search "BRAF V600E" or gene name |
COSMIC_get_mutations_by_gene |
gene OR gene_name, max_results |
All mutations for a gene |
PharmacoDB_get_cell_line |
operation="get_cell_line", cell_name |
Cell line metadata + datasets |
PharmacoDB_get_experiments |
operation="get_experiments", compound_name, cell_line_name, dataset_name, per_page |
Drug response data (IC50, AAC, EC50) |
PharmacoDB_get_biomarker_assoc |
operation="get_biomarker_associations", compound_name, tissue_name, mdata_type, per_page |
Gene-drug sensitivity correlations |
PharmacoDB_search |
operation="search", query |
Find PharmacoDB IDs |
CellMarker_search_cancer_markers |
operation="search_cancer_markers", cancer_type, gene_symbol, cell_type |
Cancer cell markers |
CellMarker_search_by_gene |
operation="search_by_gene", gene_symbol (required), species |
Cell types expressing a gene |
HPA_get_comparative_expression_by_gene_and_cellline |
gene_name (required), cell_line (required) |
Supported lines: ishikawa, hela, mcf7, a549, hepg2, jurkat, pc3, rh30, siha, u251 |
SYNERGxDB_search_combos |
drug_name_1, drug_name_2, sample (tissue or cell ID) |
Drug combination synergy (ZIP, Bliss, Loewe) |
SYNERGxDB_list_cell_lines |
- | All cell lines in SYNERGxDB |
DGIdb_get_drug_gene_interactions |
genes: list[str] |
Druggable gene interactions |
OpenTargets_get_associated_drugs_by_target_ensemblID |
ensemblId, size |
Drugs targeting a gene |
STRING_get_network |
protein_ids: list[str], species: int (9606) |
PPI network for gene context |
MyGene_query_genes |
query (NOT q) |
Resolve gene symbol to Ensembl ID |
cBioPortal_get_mutations |
study_id, gene_list (STRING, not array) |
Cell line mutations from CCLE |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 6d ago Changed · -4 lines fbfa867c323c
- 11d ago First seen · 280 lines · 100 tokens per session scan A 895d6d103fed
tooluniverse-cell-line-profiling is a skill published in the GitHub repository mims-harvard/ToolUniverse (1,680 stars, last pushed 2d ago), licensed Apache-2.0. It adds 100 tokens to every session and 5,011 once invoked, about $0.0005 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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