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tooluniverse-stem-cell-organoid

Stem cell, iPSC, and organoid research — pluripotency markers, differentiation protocol pathways, lineage commitment factors, organoid model selection. Use for iPSC characterization, differentiation protocol design via developmental-pathway recapitulation, and organoid-model selection for disease modeling.

72

Quality

88%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

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 multi-phase workflow and concrete tooling, but it carries some redundant concept explanation and is monolithic where a few reference files would aid navigation.

Suggestions

Trim the 'Reasoning Strategy' opening paragraph to tool-relevant operational rules, dropping general developmental-biology exposition Claude already knows.

Move the detailed signaling-pathway table and organoid-fidelity scoring matrix into a separate references/ file (e.g. PATHWAYS.md) and link to it from SKILL.md to improve progressive disclosure.

Add an explicit validation/verification step in the workflow (e.g. cross-check retrieved CellMarker sets against a known reference before scoring evidence) to strengthen feedback loops.

DimensionReasoningScore

Conciseness

The 'Reasoning Strategy' paragraph explains developmental-biology concepts Claude largely already knows (dual SMAD inhibition, WNT activation-then-inhibition, growth-factor timing), which is mostly efficient but could be tightened to tool-relevant specifics only.

2 / 3

Actionability

It gives executable guidance: concrete tools with required parameters ('operation="search_by_cell_type", cell_name='), KEGG IDs, named modulators (CHIR99021, IWP-2), and a runnable Python snippet in Phase 3.

3 / 3

Workflow Clarity

The Phase 0–5 sequence is clearly laid out with a 'LOOK UP DON'T GUESS' checkpoint and a synthesis-question checklist; the work is analytical rather than destructive, so no feedback-loop cap applies.

3 / 3

Progressive Disclosure

The skill is a single 150+ line monolithic file with no bundle references; the detailed pathway and organoid-fidelity tables are well-organized but inline and could be split into separate reference files for easier navigation.

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, trigger-rich, and clearly answers both 'what' and 'when' in third person, hitting the top anchor on every dimension. It is concise without padding.

DimensionReasoningScore

Specificity

The description lists multiple concrete capabilities — 'pluripotency markers, differentiation protocol pathways, lineage commitment factors, organoid model selection' — rather than vague language, matching the score-3 anchor.

3 / 3

Completeness

It states both what it does (marker/pathway/lineage/organoid research) and when to use it via an explicit 'Use for iPSC characterization, differentiation protocol design …' trigger clause, in third person.

3 / 3

Trigger Term Quality

It uses natural terms a researcher would actually say — 'stem cell', 'iPSC', 'organoid', 'disease modeling' — giving good coverage rather than jargon.

3 / 3

Distinctiveness Conflict Risk

The stem-cell/iPSC/organoid niche with developmental-pathway recapitulation triggers is clearly distinct and unlikely to fire for unrelated skills.

3 / 3

Total

12

/

12

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
mims-harvard/ToolUniverse
Reviewed

Table of Contents

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