heatmap-beautifier
Professional beautification tool for gene expression heatmaps, automatically adds clustering trees, color annotation tracks, and intelligently optimizes label layout.
65
57%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./scientific-skills/Data analysis/heatmap-beautifier/SKILL.mdQuality
Discovery
50%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 excels at specificity and carves out a clear niche for gene expression heatmap beautification with concrete features. However, it critically lacks any 'Use when...' guidance, which would help Claude know when to select this skill from a large skill library. The trigger terms are domain-appropriate but could include more user-facing variations.
Suggestions
Add a 'Use when...' clause with explicit triggers like 'Use when the user needs to visualize gene expression data, create publication-ready heatmaps, or mentions RNA-seq, microarray, or expression matrices.'
Include common user terms and file formats such as 'heatmap', 'expression matrix', 'RNA-seq', 'microarray', '.csv', or 'clustering visualization' to improve trigger term coverage.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'adds clustering trees, color annotation tracks, and intelligently optimizes label layout' - these are precise, technical capabilities for heatmap beautification. | 3 / 3 |
Completeness | Describes what the skill does well, but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. | 1 / 3 |
Trigger Term Quality | Includes relevant domain terms like 'gene expression heatmaps', 'clustering trees', 'annotation tracks', but missing common user variations like 'heatmap', 'expression data', 'RNA-seq visualization', or file formats. | 2 / 3 |
Distinctiveness Conflict Risk | Very clear niche - 'gene expression heatmaps' with specific features like 'clustering trees' and 'annotation tracks' makes this highly distinct and unlikely to conflict with other visualization or data skills. | 3 / 3 |
Total | 9 / 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 strong actionable guidance with executable code examples, comprehensive parameter documentation, and useful demo mode for verification. However, it suffers from verbosity in meta-sections about response formatting that don't belong in a tool skill, and the workflow section is too abstract to guide multi-step heatmap generation effectively.
Suggestions
Remove or significantly condense the 'Output Requirements' and 'Response Template' sections - these describe Claude's response behavior rather than tool usage and waste tokens.
Rewrite the 'Workflow' section to be specific to heatmap generation with concrete validation steps, e.g., '1. Validate CSV has gene rows/sample columns 2. Run with --demo to verify environment 3. Generate heatmap 4. Verify output file exists and opens correctly'.
Move the detailed parameter table and color scheme reference to a separate REFERENCE.md file, keeping only essential parameters inline.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill contains some unnecessary verbosity, particularly in the 'Output Requirements' and 'Response Template' sections which describe how Claude should respond rather than how to use the tool. The error handling section also over-explains concepts Claude already understands. | 2 / 3 |
Actionability | Provides fully executable code examples for both Python API and command line usage, complete with copy-paste ready commands, parameter tables, and concrete CSV format examples. The demo mode allows immediate verification. | 3 / 3 |
Workflow Clarity | The workflow section is abstract and generic rather than specific to heatmap generation. While fallback behavior is documented, the main workflow lacks explicit validation checkpoints between steps (e.g., validate CSV format before processing, verify output file was created). | 2 / 3 |
Progressive Disclosure | Content is reasonably organized with clear sections, but the document is somewhat monolithic. The parameter table and detailed error handling could be split into reference files. No external file references are provided for advanced topics like annotation track configuration. | 2 / 3 |
Total | 9 / 12 Passed |
Validation
90%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
Table of Contents
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