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hierarchical-clustering-plot

Use when building a sample-level hierarchical clustering dendrogram from a bulk expression matrix and sample annotation table, especially for QC, batch inspection, or sample similarity assessment. Trigger keywords: hierarchical clustering, dendrogram, sample QC, batch inspection, sample similarity. NOT for: differential expression testing, gene clustering heatmaps, single-cell clustering workflows.

Quality

88%

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SKILL.md
Quality
Evals
Security

Quality

Content

88%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.

A highly actionable, well-structured CLI skill body with executable commands, complete argument and input-format documentation, sequenced validation-first workflow steps, and an error-recovery table wired to a troubleshooting reference. Weaknesses are minor: dev-oriented checklist/date padding and references to a tests/ directory that is not present in the bundle.

Suggestions

Remove or relocate the 'Implementation Checklist' and the '*Last updated: 2026-04-16 | Version: 1.0.0*' stamp; they are development bookkeeping and time-sensitive metadata that consume tokens without helping execution.

Consolidate the 'When to Read External Files' table with the per-step 'WHEN..., READ:' lines to eliminate duplicated navigation guidance.

Ship the referenced tests/ files (tests/data/, tests/run_tests.R, tests/testthat/test-clustering.R) or update the SKILL.md references and example commands to paths that exist in the bundle.

DimensionReasoningScore

Conciseness

The body is dense with high-value tables (Arguments, Output Files, Error Handling) and never explains concepts Claude already knows. Minor trimming is needed: the 19-item 'Implementation Checklist' is dev bookkeeping, the '*Last updated: 2026-04-16 | Version: 1.0.0*' stamp is time-sensitive information penalized outside a deprecation section, and the 'When to Read External Files' table partially duplicates the per-step 'WHEN..., READ:' lines. Mostly efficient with minor over-explanation fits the 4 anchor better than 3 or 5.

4 / 5

Actionability

Fully executable guidance throughout: exact 'Rscript scripts/main.R' invocations with every flag, an arguments table with defaults and enumerated valid values, concrete CSV input examples with sample rows, named output files, and post-run validation commands ('ls -la ./output/hierarchical_clustering_plot.pdf', 'wc -l ./output/clustering_order.csv'). Copy-paste ready and covering the common cases, matching the 5 anchor.

5 / 5

Workflow Clarity

Four clearly sequenced steps open with 'Step 1: Validate Input', the error table pairs each SKILL_* code with Cause and Solution columns plus anchor links, and 'IF error persists, READ: references/troubleshooting.md' provides an explicit escalation/feedback loop, supplemented by verification commands. This is a read-only analysis (not destructive/batch), so the validation cap does not apply; explicit checkpoints and error-recovery loops match the 5 anchor.

5 / 5

Progressive Disclosure

The 'When to Read External Files' table provides situation-based navigation one level deep, and all cited references/ and scripts/ files exist and match their descriptions. However, 'tests/data/', 'tests/run_tests.R', and 'tests/testthat/test-clustering.R' are referenced in the navigation table, examples, and testing section but absent from the bundle, and the basic example command depends on the missing test fixture. Good structure with concrete dangling-path gaps fits the 4 anchor rather than the fully navigable 5 anchor.

4 / 5

Total

18

/

20

Passed

Description

82%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 well-crafted description with explicit what/when structure, natural trigger keywords, and clear negative boundaries against adjacent skills. Its main weakness is that it names only one concrete action, underselling the workflow's outputs (distance matrix, clustering order, matched samples).

Suggestions

Mention the concrete outputs in the description (e.g., '...dendrogram and pairwise sample distance matrix') so the capability list covers more than the single build-a-dendrogram action.

Add one or two common synonyms such as 'sample clustering' or 'cluster samples' to the trigger keyword list to broaden natural-term coverage.

DimensionReasoningScore

Specificity

"building a sample-level hierarchical clustering dendrogram from a bulk expression matrix and sample annotation table" names the domain and one concrete action, but lists no further actions or outputs (e.g., distance matrix export, leaf-order CSV). Matches the anchor for 1-2 concrete actions without comprehensive coverage; not 4 because 'several specific actions' are absent, not 2 because the named action is concrete rather than generic.

3 / 5

Completeness

Explicitly answers what ("building a sample-level hierarchical clustering dendrogram from a bulk expression matrix and sample annotation table") and when ("especially for QC, batch inspection, or sample similarity assessment" plus a concrete trigger keyword list). Matches the anchor requiring both what and when with concrete trigger phrases; the 4 anchor's weaker 'when' does not apply.

5 / 5

Trigger Term Quality

"Trigger keywords: hierarchical clustering, dendrogram, sample QC, batch inspection, sample similarity" are natural phrases a user would actually say. A few natural variants are missing (e.g., 'sample clustering', 'cluster samples') and there are no file-extension hooks, so it falls short of the comprehensive 5 anchor but sits well above the generic 1-2 keyword anchors.

4 / 5

Distinctiveness Conflict Risk

"NOT for: differential expression testing, gene clustering heatmaps, single-cell clustering workflows" draws explicit negative boundaries around a tight niche (sample-level bulk-expression dendrograms), minimizing wrong-skill triggers. Fits the clear-niche 5 anchor; the 4 anchor's 'minor overlap risk' is precluded by the explicit exclusions.

5 / 5

Total

17

/

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

aipoch/medical-research-skills

Path

awesome-med-research-skills/Data Analysis/hierarchical-clustering-plot/SKILL.md

Reviewed

Table of Contents

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