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tooluniverse-gene-regulatory-networks

Gene regulatory network analysis — TF-target inference (JASPAR motifs, ChIP-seq), motif scanning, eQTL integration, perturbation evidence (knockout/overexpression). Use for 'which TF regulates gene X', 'which genes does TF Y target', regulatory pathway reconstruction. Distinguishes direct (binding) vs indirect (co-expression) regulatory evidence.

74

Quality

91%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

The canonical home for this skill is tooluniverse-gene-regulatory-networks in mims-harvard/ToolUniverse

SKILL.md
Quality
Evals
Security

Quality

Content

82%Weight 40%Scale 1-5

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

The content is a strong, actionable tool catalog with excellent concrete examples and clear sequencing. Its main weaknesses are mild verbosity in the framing prose and implicit rather than explicit per-phase validation checkpoints.

Suggestions

Tighten the opening evidence-hierarchy paragraph — the per-tier T1–T4 grading near the end already conveys this; lead with the workflow instead.

Add an explicit per-phase validation checkpoint (e.g., 'verify matrix_id exists before calling jaspar_get_matrix') rather than relying on the post-hoc Evidence Grading section.

Consider moving the bulk tool reference (parameters + return schemas) into a references/TOOLS.md file, keeping SKILL.md as an overview with well-signaled one-level links.

DimensionReasoningScore

Conciseness

The body is dense and mostly earns its tokens with tool-specific knowledge Claude would not know, but the opening evidence-hierarchy paragraph and some inline parameter tables could be trimmed slightly. Efficient overall, just above the midpoint.

4 / 5

Actionability

Provides concrete tool names, exact parameter lists, copy-paste JSON call examples, and return-shape schemas for every tool, plus five concrete use-pattern sequences — fully executable guidance for a tool-calling skill.

5 / 5

Workflow Clarity

Eight numbered phases (0–7) are clearly sequenced with a Phase 0 disambiguation step and a Common Mistakes section, but per-phase validation checkpoints are implicit (Evidence Grading is post-hoc) rather than explicit validate-then-retry loops.

4 / 5

Progressive Disclosure

Well-organized with clear section headers and one-level structure (no nested references), though a large tool catalog is inlined rather than split into separate reference files; no bundle files exist so structure is purely inline and reasonably placed.

4 / 5

Total

17

/

20

Passed

Description

100%Weight 40%Scale 1-5

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 exemplary: it states concrete capabilities, includes natural-language trigger phrases users would actually say, and explicitly separates the 'what' from the 'when' in a distinct niche. No ambiguity or fluff.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "TF-target inference (JASPAR motifs, ChIP-seq)", "motif scanning", "eQTL integration", "perturbation evidence" — with comprehensive coverage of the domain, matching the top anchor.

5 / 5

Completeness

Explicitly states what ("Gene regulatory network analysis — TF-target inference...") and when ("Use for 'which TF regulates gene X'...") with concrete trigger phrases, matching the top anchor.

5 / 5

Trigger Term Quality

Embeds natural user phrasing in quotes ("which TF regulates gene X", "which genes does TF Y target") alongside domain keywords (motif, eQTL, regulatory pathway), giving comprehensive natural-term coverage.

5 / 5

Distinctiveness Conflict Risk

Occupies a clear niche (gene regulatory network analysis) with domain-specific triggers unlikely to fire for unrelated skills, minimizing conflict risk.

5 / 5

Total

20

/

20

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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