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bio-database-evidence

Unified biological database evidence owner. Use for gene annotation, variant clinical significance, cancer mutation evidence, GWAS trait associations, pathway mapping, target-disease evidence, protein structures, protein interaction networks, reference single-cell census queries, and cross-database biological ID mapping. Do not use for full single-cell analysis, bulk RNA-seq differential expression, BAM/VCF processing, protein embedding models, metabolic flux modeling, genomic interval ML, or flow-cytometry file parsing.

72

Quality

89%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

78%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 body is concise and well-structured with appropriate one-level-deep progressive disclosure, but the workflow is guidance-level rather than executable and lacks explicit validation checkpoints for multi-source evidence gathering.

Suggestions

Add one concrete per-source query example or API call pattern in the body (or a quick-start snippet) so Claude has executable guidance without needing the reference for the common case.

Make workflow checkpoints explicit, e.g. after step 2 add a verify step confirming the chosen source returned evidence before proceeding to cross-database mapping or table assembly.

Inline the multi-source output table column schema (currently only in the reference) into the body, since it is the core deliverable pattern for this skill.

DimensionReasoningScore

Conciseness

Lean, well-organized body with tight bullet lists and no padding or explanation of concepts Claude already knows; every section earns its place.

5 / 5

Actionability

The workflow gives procedural hints ('Pick the narrowest source', 'Preserve source names, query terms, access dates') but the body lacks concrete executable query patterns or per-source API guidance; the concrete output table pattern lives only in the reference file, leaving the body itself incomplete.

3 / 5

Workflow Clarity

A clear five-step sequence is present with a sensible order; for read-only lookups the destructive/batch validation cap does not apply, but checkpoints (e.g. verifying a source returned evidence before cross-mapping) remain implicit rather than explicit.

4 / 5

Progressive Disclosure

Clean overview structure (Use For / Do Not Use For / Workflow / Source Guide) with a single one-level-deep reference, references/database-evidence-sources.md, which exists and is clearly signaled.

5 / 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 specific, complete, and distinctive, with concrete trigger terms and an explicit use/don't-use boundary that cleanly separates it from neighboring skills. No first/second-person voice and no vague fluff.

DimensionReasoningScore

Specificity

Lists multiple concrete capabilities across nine domains ("gene annotation", "variant clinical significance", "GWAS trait associations", "protein structures", "cross-database biological ID mapping"), giving comprehensive coverage rather than vague abstraction.

5 / 5

Completeness

Explicitly answers both 'what' (unified biological database evidence owner with enumerated capabilities) and 'when' ('Use for ...' trigger clause), reinforced by a 'Do not use for ...' boundary list.

5 / 5

Trigger Term Quality

Comprehensive natural terms including database names and synonyms users actually say (ClinVar, COSMIC, GWAS Catalog, AlphaFold DB, STRING, Reactome, KEGG, Open Targets, CELLxGENE Census), plus concrete trigger phrasing in the 'Use for' clause.

5 / 5

Distinctiveness Conflict Risk

Clear niche of biological database evidence with distinct triggers and an explicit negative-boundary list redirecting adjacent tasks (scanpy, pydeseq2, BAM/VCF, metabolic modeling) to other 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
foryourhealth111-pixel/Vibe-Skills
Reviewed

Table of Contents

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