multi-panel-figure-assembler
Automatically assemble 6 sub-figures (A-F) into a high-resolution composite figure with aligned edges, unified fonts, and labels.
Install with Tessl CLI
npx tessl i github:aipoch/medical-research-skills --skill multi-panel-figure-assembler65
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
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, distinctive niche for scientific figure assembly. However, it critically lacks any 'Use when...' guidance, making it difficult for Claude to know when to select this skill from a large pool. The trigger terms could also be expanded to include common user phrasings.
Suggestions
Add a 'Use when...' clause with trigger terms like 'combine figures', 'panel figure', 'multi-panel layout', 'scientific figure', 'figure assembly'
Include common file format mentions users might reference (e.g., 'PNG', 'TIFF', 'publication-ready figures')
Consider adding context about the domain (e.g., 'for scientific publications' or 'journal figures') to help Claude match user intent
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'assemble 6 sub-figures (A-F)', 'high-resolution composite figure', 'aligned edges', 'unified fonts', and 'labels'. These are precise, actionable capabilities. | 3 / 3 |
Completeness | Describes WHAT it does well but completely lacks a 'Use when...' clause or any explicit trigger guidance. Per rubric guidelines, missing explicit trigger guidance caps completeness at 2, and this has none at all. | 1 / 3 |
Trigger Term Quality | Contains some relevant terms like 'sub-figures', 'composite figure', 'labels', but misses common user variations like 'panel figure', 'figure layout', 'multi-panel', 'scientific figure', or file format mentions. | 2 / 3 |
Distinctiveness Conflict Risk | Very specific niche: assembling exactly 6 sub-figures (A-F) into composites with specific formatting requirements. Unlikely to conflict with general image editing or document 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.
The skill provides good actionable guidance with executable examples for both CLI and Python usage. However, it suffers from redundancy (duplicate parameter tables) and unnecessary boilerplate sections that don't help Claude use the tool. The core functionality documentation is solid but buried under template-like content that should be removed.
Suggestions
Remove the duplicate Parameters table - the Command Line Arguments table already covers this with more detail
Remove or relocate boilerplate sections (Risk Assessment, Security Checklist, Evaluation Criteria, Lifecycle Status) that don't help Claude execute the task
Add error handling guidance - what to do if images fail to load, have incompatible formats, or if the output looks wrong
Add a quick validation step to verify output quality (e.g., check file size, open and inspect result)
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Contains significant redundancy - the Parameters table duplicates the Command Line Arguments table with less information. The Risk Assessment, Security Checklist, Evaluation Criteria, and Lifecycle Status sections add boilerplate that doesn't help Claude use the tool. Could be tightened considerably. | 2 / 3 |
Actionability | Provides fully executable command-line examples and Python code that are copy-paste ready. Clear argument tables with defaults and descriptions. Both CLI and programmatic usage patterns are concrete and complete. | 3 / 3 |
Workflow Clarity | This is a single-command tool, so complex workflows aren't needed. However, there's no validation guidance - what happens if images have incompatible formats? No error handling examples or verification steps for checking output quality before using in publications. | 2 / 3 |
Progressive Disclosure | Content is reasonably organized with clear sections, but everything is in one monolithic file. The boilerplate sections (Risk Assessment, Security Checklist, Evaluation Criteria, Lifecycle Status) clutter the main content and could be removed or moved elsewhere. No references to external documentation. | 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 | |
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.