tooluniverse-cell-line-profiling

Cancer cell-line selection and profiling for experimental model choice. Cross-references DepMap, Cellosaurus, COSMIC, PharmacoDB to deliver identity verification, mutation/CNV profile, gene dependencies, drug sensitivities, and druggable targets. Use to answer 'which cell line should I use for studying gene X?' or 'is this cell line a good model for cancer Y?'. Outputs ranked recommendations with rationale, growth characteristics, and known pitfalls.

Quality

88%

Does it follow best practices?

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Securityby

Low

Low-risk findings worth noting

Quality

Content

77%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is highly actionable with a clear phased workflow, concrete tool calls, and verification checkpoints, but it is somewhat verbose and monolithic, keeping large reference tables inline rather than splitting them into separate files.

Suggestions

Trim the generic 'KEY PRINCIPLES', 'LOOK UP, DON'T GUESS', and 'COMPUTE, DON'T DESCRIBE' sections or fold their essentials into the workflow steps to reduce boilerplate tokens.

Move the large 'Tool Parameter Reference' and 'Quick Reference: Common Cancer Cell Lines by Type' tables into separate reference files (e.g. references/tool_parameters.md, references/cell_line_quick_reference.md) and link to them, improving progressive disclosure.

De-duplicate tool-call signatures that appear in both the Phase 0 reference table and the per-phase walkthroughs by citing the reference table from the phases.

Dimension	Reasoning	Score
Conciseness	The body is dense with actionable specifics rather than concept explanations, but the generic 'KEY PRINCIPLES' list and the 'LOOK UP, DON'T GUESS' / 'COMPUTE, DON'T DESCRIBE' sections are boilerplate that could be tightened, fitting the score-2 anchor.	2 / 3
Actionability	Throughout the phases it gives fully executable tool calls with exact parameters (e.g. 'cellosaurus_search_cell_lines(q="id:<NAME>")') and copy-paste bash for the bundled script, matching the score-3 anchor for copy-paste-ready guidance.	3 / 3
Workflow Clarity	A clearly sequenced Phase 0–5 workflow with an explicit completeness checklist as a validation checkpoint, plus an error-handling table and DepMap fallbacks as feedback loops, satisfies the score-3 anchor.	3 / 3
Progressive Disclosure	Sections are well organized and the one bundled reference (scripts/depmap_gene_dependency.py) is real and clearly signaled at one level deep, but the file is monolithic at ~280 lines with large inline reference tables (tool parameters, cell-line quick reference) that could be split out, matching the score-2 anchor.	2 / 3
	Total	10 / 12 Passed

Description

100%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is specific, third-person, and answers both what the skill does and when to use it, with natural trigger phrasings and a distinct niche. It matches the strongest anchors on every dimension.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'identity verification, mutation/CNV profile, gene dependencies, drug sensitivities, and druggable targets' plus 'ranked recommendations with rationale, growth characteristics, and known pitfalls' — matching the score-3 anchor for multiple specific concrete actions.	3 / 3
Completeness	Explicitly answers both what (selection/profiling, identity, dependencies, drug sensitivities, targets) and when ('Use to answer...') with an explicit trigger clause, satisfying the score-3 anchor.	3 / 3
Trigger Term Quality	Includes natural phrasings a user would actually say — 'which cell line should I use for studying gene X?' and 'is this cell line a good model for cancer Y?' — giving good coverage of natural trigger terms.	3 / 3
Distinctiveness Conflict Risk	Occupies a clear niche — cancer cell-line selection/profiling cross-referencing DepMap, Cellosaurus, COSMIC, PharmacoDB — with distinct triggers unlikely to fire for unrelated skills.	3 / 3
	Total	12 / 12 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: mims-harvard/ToolUniverse
Path: plugin/skills/tooluniverse-cell-line-profiling/SKILL.md
Commit: 089eb8e

Reviewed: about 8 hours ago

Table of Contents

Discovery Implementation Validation

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