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batch-effect-correction

Use when correcting batch effects in merged bulk expression matrices with sample-level batch metadata while preserving biological group structure and generating before-and-after QC plots. NOT for: single-cell integration, raw FASTQ processing, differential expression without batch labels, or datasets without biological groups.

Quality

86%

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SKILL.md
Quality
Evals
Security

Quality

Content

81%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 highly actionable with a clear, validated workflow and exemplary reference routing, but it carries redundant sections and references a tests/data/ bundle that does not actually exist. Tightening the duplicated validation content and either shipping the test data or removing those references would lift the skill's overall quality.

Suggestions

Either bundle the referenced tests/data/expression_matrix_merged.csv and tests/data/sample_info.csv or remove the tests/data/ row from the file table, the Testing example commands, and the 'Test data provided' checklist item — the paths currently point at files that do not exist.

Merge the 'Input Validation' section with 'Input Format', since both state the same acceptance criteria (2 groups, 2 batches, 2 samples per group/batch, unique non-empty IDs).

Remove the 'Implementation Checklist' section (author-facing, not agent-facing) and the 'Last updated / Version' footer to reduce token spend without losing operational value.

DimensionReasoningScore

Conciseness

Most of the body is dense, operational tables (arguments, outputs, errors, examples), but the 'Input Validation' section restates requirements already in 'Input Format', the 'Implementation Checklist' is author-facing padding, and the prerequisites note duplicates the install command. This fits anchor 3 ('mostly efficient but some unnecessary explanation or could be tightened') better than anchor 4, since two whole sections are redundant rather than minor phrasing.

3 / 5

Actionability

Fully executable, copy-paste-ready commands: the full CLI invocation with all flags, an argument table with defaults, concrete CSV input examples, three usage examples covering common cases, error codes with solutions, and test commands. This matches anchor 5.

5 / 5

Workflow Clarity

Clear sequence (prerequisites -> run -> verify outputs -> report per the Agent Response Contract) with explicit validation (Step 1 'Validate Input' plus Testing validation commands) and a feedback loop for error recovery ('IF error persists, READ references/troubleshooting.md', plus the dependency-first troubleshooting note). This matches anchor 5 rather than 4, which would require missing checkpoints.

5 / 5

Progressive Disclosure

The 'When to Read External Files' situation-based table provides well-signaled, one-level-deep references that all exist (references/algorithm.md, scripts/main.R, references/troubleshooting.md, references/cli-guide.md). However, 'tests/data/' is referenced in the table and the Testing section (with specific filenames) and asserted as provided in the checklist, yet no tests/ directory exists in the bundle — a broken path that keeps this below anchor 5.

4 / 5

Total

17

/

20

Passed

Description

87%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.

A strong, well-scoped description: it states concrete capabilities, an explicit 'Use when' trigger, and a NOT-for list that sharply reduces mis-triggering against adjacent bioinformatics skills. The only improvement space is adding a few synonyms (e.g., 'batch correction', 'ComBat') for broader natural-language matching.

DimensionReasoningScore

Specificity

The description names the domain ('merged bulk expression matrices with sample-level batch metadata') and several concrete actions ('correcting batch effects', 'preserving biological group structure', 'generating before-and-after QC plots'). It falls short of anchor 5 because it omits the method (ComBat/limma), normalization, and file formats, leaving minor gaps in coverage.

4 / 5

Completeness

It explicitly answers both what ('correcting batch effects... while preserving biological group structure and generating before-and-after QC plots') and when ('Use when correcting batch effects...') with concrete trigger phrases, and adds a NOT-for exclusion list. This matches anchor 5; anchor 4 would require a weaker or less specific 'when' clause.

5 / 5

Trigger Term Quality

Natural user phrases like 'batch effects', 'batch metadata', 'merged bulk expression matrices', 'QC plots', plus exclusion terms ('single-cell integration', 'raw FASTQ processing', 'differential expression') give good keyword coverage. A few natural synonyms are missing ('batch correction' as a noun phrase, 'ComBat', '.csv'), so it is not anchor 5.

4 / 5

Distinctiveness Conflict Risk

A clear niche (bulk expression batch correction with sample-level batch labels) with explicit exclusions for single-cell integration, FASTQ processing, and label-free differential expression gives minimal conflict risk, matching anchor 5.

5 / 5

Total

18

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

aipoch/medical-research-skills

Path

awesome-med-research-skills/Data Analysis/batch-effect-correction/SKILL.md

Reviewed

Table of Contents

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