wgcna-analysis

Use when building a weighted gene co-expression network from a bulk expression matrix and a sample group file, filtering variable genes by MAD, identifying co-expression modules with WGCNA, correlating modules with traits, and exporting module-level plots and gene tables. NOT for single-cell RNA-seq, differential expression testing, methylation analysis, or datasets that are too small for WGCNA after quality control.

Quality

87%

Does it follow best practices?

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Securityby

Passed

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Quality

Content

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

A well-structured, highly actionable skill body with a clear external-file navigation table, full CLI reference, and validation tooling. Main gaps are dangling references to non-existent files (diagnosis-report.md, tests/) and validation that lives outside the workflow steps rather than as inline checkpoints.

Suggestions

Remove or fix the references to missing files (references/diagnosis-report.md, tests/data/, tests/validate_outputs.R) from the navigation table and Testing section so all pointers resolve.

Add explicit validation checkpoints inside the Workflow steps (e.g. 'Validate outputs with tests/validate_outputs.R after Step 5') rather than only in the separate Testing section.

De-duplicate the full-flag usage block against the Arguments table to trim tokens, keeping one canonical form.

Dimension	Reasoning	Score
Conciseness	Information-dense with no padding of concepts Claude already knows (WGCNA, R, PDFs), though the full-flag usage block and the arguments table overlap somewhat; minor tightening possible.	4 / 5
Actionability	Fully executable: a copy-paste Rscript command with every flag, concrete CSV input examples, a smoke-test command, and a validation script covering the common cases.	5 / 5
Workflow Clarity	A clearly sequenced five-step workflow with validation present (validate_outputs.R, error table with retry guidance, additional-verification checklist), but validation checkpoints are not embedded inline between the workflow steps.	4 / 5
Progressive Disclosure	Excellent one-level navigation via the "When to Read External Files" table and well-split bundle files, but it references references/diagnosis-report.md, tests/data/, and tests/validate_outputs.R which are not present in the bundle.	4 / 5
	Total	17 / 20 Passed

Description

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

A highly specific, well-targeted description that clearly states capabilities, when to trigger, and when not to use it. Minor room for additional natural synonyms or file extensions in the trigger terms.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions ("filtering variable genes by MAD", "identifying co-expression modules with WGCNA", "correlating modules with traits", "exporting module-level plots and gene tables"), matching the comprehensive-coverage anchor.	5 / 5
Completeness	Explicitly answers both what (build network, filter, identify modules, correlate, export) and when ("Use when building a weighted gene co-expression network..."), plus an explicit when-not clause, matching the both-what-and-when anchor.	5 / 5
Trigger Term Quality	Strong domain terms a bioinformatician would naturally say ("weighted gene co-expression network", "bulk expression matrix", "WGCNA", "single-cell RNA-seq", "methylation analysis"), though a few common synonyms or file extensions are absent; third-person voice is correct.	4 / 5
Distinctiveness Conflict Risk	Clear niche (bulk WGCNA co-expression) with an explicit "NOT for single-cell RNA-seq, differential expression testing, methylation analysis" exclusion, giving minimal conflict risk.	5 / 5
	Total	19 / 20 Passed

Validation

87%

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 — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning
referenced_paths_exist	Referenced path issues: 1 missing	Warning

	Total	14 / 16 Passed

Repository: aipoch/medical-research-skills
Path: awesome-med-research-skills/Data Analysis/wgcna-analysis/SKILL.md
Commit: f5ef65b

Reviewed: ~9 hours ago

Table of Contents

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