upset-plot-converter

Convert complex Venn diagrams with more than 4 sets into clearer UpSet plots for publication-ready set intersection visualization.

Quality

66%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./scientific-skills/Data analysis/upset-plot-converter/SKILL.md

Quality

Discovery

67%

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

This description excels at specificity and distinctiveness, clearly defining a narrow visualization conversion task. However, it lacks an explicit 'Use when...' clause and could benefit from additional trigger terms that users might naturally use when requesting this type of visualization work.

Suggestions

Add a 'Use when...' clause with trigger terms like 'too many sets', 'complex overlaps', 'set visualization', or 'intersection analysis'

Include common variations users might say such as 'overlapping sets', 'multi-set comparison', or mention relevant file formats/tools (e.g., 'R', 'Python', 'matplotlib')

Dimension	Reasoning	Score
Specificity	Lists specific concrete actions: 'Convert complex Venn diagrams', 'more than 4 sets', 'UpSet plots', 'publication-ready set intersection visualization'. Multiple specific capabilities are clearly stated.	3 / 3
Completeness	Clearly answers 'what' (convert Venn diagrams to UpSet plots for publication), but lacks an explicit 'Use when...' clause. The when is only implied through the description of the conversion task.	2 / 3
Trigger Term Quality	Includes good terms like 'Venn diagrams', 'UpSet plots', 'set intersection', but missing common variations users might say like 'overlapping sets', 'set comparison', 'intersection chart', or file format mentions.	2 / 3
Distinctiveness Conflict Risk	Highly distinctive niche combining 'Venn diagrams', 'UpSet plots', and 'set intersection visualization'. Very unlikely to conflict with other skills due to the specific visualization domain.	3 / 3
	Total	10 / 12 Passed

Implementation

64%

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

This skill provides good actionable code examples and clear parameter documentation, making it immediately usable for UpSet plot generation. However, it suffers from verbosity with generic process templates (Response Template, Fallback Template, Output Requirements) that add significant token overhead without skill-specific value. The workflow section describes meta-process rather than the actual data-to-plot conversion steps.

Suggestions

Remove or drastically compress the Response Template, Fallback Template, and Output Requirements sections - these are generic process instructions Claude doesn't need

Replace the abstract 5-step Workflow with concrete UpSet-specific steps: validate set data → compute intersections → configure plot parameters → generate figure → verify output

Add a validation checkpoint after data loading (e.g., 'Verify all sets have at least 1 element before proceeding')

Dimension	Reasoning	Score
Conciseness	The skill contains useful content but is verbose with redundant sections (Output Requirements, Response Template, Fallback Template) that add process overhead Claude doesn't need. The workflow and error handling sections repeat concepts and could be significantly tightened.	2 / 3
Actionability	Provides fully executable Python code examples, clear parameter tables, and copy-paste ready commands for both quick checks and inline testing. The usage example is concrete and immediately usable.	3 / 3
Workflow Clarity	The workflow section lists steps but they are generic process steps rather than specific to UpSet plot generation. Missing explicit validation checkpoints between data loading and plot generation. Error handling mentions fallbacks but doesn't integrate them into a clear sequence.	2 / 3
Progressive Disclosure	Content is reasonably organized with clear sections, but everything is inline in one file when the Response Template, Fallback Template, and Output Requirements could be separate references. No external file references despite the skill's complexity warranting them.	2 / 3
	Total	9 / 12 Passed

Validation

90%

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 — 10 / 11 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	10 / 11 Passed

Repository: aipoch/medical-research-skills
Commit: ca9aaa4

Reviewed: 27 days ago

Table of Contents

Discovery Implementation Validation

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