heatmap-beautifier

Professional beautification tool for gene expression heatmaps, automatically adds clustering trees, color annotation tracks, and intelligently optimizes label layout.

Quality

54%

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Securityby

Passed

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tessl review fix ./scientific-skills/Data Analysis/heatmap-beautifier/SKILL.md

Quality

Content

50%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 delivers concrete, mostly executable heatmap guidance but is weighed down by generic boilerplate and cross-reference placeholders that pad the token budget. Workflow checkpoints and reference signaling are present but incomplete.

Suggestions

Remove the 'See ## X above for related details' placeholder lines and the generic boilerplate sections (Risk Assessment, Security Checklist, Response Template, Output Contract, Validation rules) that do not add heatmap-specific value.

Reconcile the CLI flag names between the 'Command Line Usage' example (--input/--output) and the 'Parameters' table (--data-path/--output-path) so the guidance is consistently executable.

Add an explicit validation step after heatmap generation (e.g. verify the output file exists and opens) and link the runtime_checklist.md by name from the body so references are clearly signaled.

Dimension	Reasoning	Score
Conciseness	The body is noticeably verbose: it repeats 'See ## X above for related details' placeholders and inlines generic boilerplate (Risk Assessment, Security Checklist, Response Template, Output Contract, Validation rules) that does not earn its tokens, matching the 'noticeably verbose; several padded sections' anchor.	2 / 5
Actionability	Concrete executable Python (HeatmapBeautifier.create_heatmap with real parameters), a parameters table, and CLI usage give mostly copy-paste-ready guidance; minor gaps from inconsistent CLI flag names (--input/--output vs --data-path/--output-path) keep it just below a 5.	4 / 5
Workflow Clarity	A sequenced workflow and a py_compile quick check exist, but there is no validation feedback loop tied to the actual file-producing heatmap generation, leaving checkpoints implicit — the 'steps listed but validation gaps' anchor.	3 / 5
Progressive Disclosure	Bundle files exist (references/runtime_checklist.md, scripts/main.py) but the body only references 'references/' generically without naming runtime_checklist.md, and substantial detail (params, color schemes, usage) is inlined rather than split out, fitting the 'some structure but references not clearly signaled' anchor.	3 / 5
	Total	12 / 20 Passed

Description

58%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 clearly states what the skill does with several concrete actions, but lacks any explicit 'when to use' trigger guidance and misses common keyword variations. It is specific to its niche with minor overlap risk against general visualization skills.

Suggestions

Add an explicit 'Use when...' clause naming natural trigger phrases users would say, e.g. 'Use when beautifying gene expression heatmaps, adding clustering trees, or annotating heatmaps with sample/gene group tracks.'

Include common keyword variations and synonyms such as plain 'heatmap' and the input format '.csv' to improve trigger-term coverage.

Mention export formats (PDF/PNG/SVG) and color schemes in the description to raise specificity toward comprehensive coverage.

Dimension	Reasoning	Score
Specificity	Names the domain and several concrete actions — 'adds clustering trees, color annotation tracks, and intelligently optimizes label layout' — fitting the 'several specific actions; minor gaps' anchor; not a 5 because export formats and color schemes are omitted.	4 / 5
Completeness	A clear 'what' is stated but there is no 'Use when...' clause or equivalent trigger guidance, which per the judging guidelines caps completeness at 3.	3 / 5
Trigger Term Quality	Domain keywords like 'gene expression heatmaps', 'clustering trees', and 'annotation tracks' are present but common variations (plain 'heatmap') and synonyms are missing, matching the 'some relevant keywords but missing variations' anchor.	3 / 5
Distinctiveness Conflict Risk	The gene-expression-heatmap niche with clustering/annotation triggers is mostly distinct, with only minor overlap risk against general plotting skills, fitting the 'mostly distinct' anchor rather than the fully-distinct 5.	4 / 5
	Total	14 / 20 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
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: scientific-skills/Data Analysis/heatmap-beautifier/SKILL.md
Commit: f5ef65b

Reviewed: ~3 hours ago

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