spatial-transcriptomics-mapper
Map spatial transcriptomics data from 10x Genomics Visium or Xenium onto tissue section images, visualizing gene expression and spatial clustering distributions.
86
Quality
83%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Quality
Discovery
82%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 is a strong, technically specific description that clearly identifies the domain (spatial transcriptomics) and concrete capabilities (mapping data, visualizing gene expression and clustering). The main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill. The domain-specific terminology provides excellent trigger terms for users in this field.
Suggestions
Add an explicit 'Use when...' clause, e.g., 'Use when analyzing Visium or Xenium data, overlaying gene expression on tissue images, or performing spatial clustering analysis.'
Consider adding file format triggers like '.h5ad', 'Space Ranger output', or 'Xenium output' that users might mention when working with this data.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'Map spatial transcriptomics data', 'visualizing gene expression', and 'spatial clustering distributions'. Also specifies concrete platforms (10x Genomics Visium, Xenium) and data types (tissue section images). | 3 / 3 |
Completeness | Clearly answers 'what does this do' with mapping and visualization capabilities, but lacks an explicit 'Use when...' clause or equivalent trigger guidance. The when is only implied through the domain-specific terminology. | 2 / 3 |
Trigger Term Quality | Includes highly specific natural keywords users in this domain would use: 'spatial transcriptomics', '10x Genomics', 'Visium', 'Xenium', 'tissue section', 'gene expression', 'spatial clustering'. These are the exact terms researchers would mention. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive niche targeting specific platforms (Visium, Xenium) and a specialized domain (spatial transcriptomics). Very unlikely to conflict with other skills due to the technical specificity. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured skill with strong actionability and workflow clarity. The CLI examples are executable and comprehensive, the fallback template provides good error recovery, and the progressive disclosure is appropriate. Minor verbosity in some sections (When to Use, redundant command examples) prevents a perfect conciseness score.
Suggestions
Remove or consolidate 'Audit-Ready Commands' section as it largely duplicates the CLI Usage examples
Trim 'When to Use' section - these use cases are self-evident from the skill description
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is reasonably efficient but includes some redundancy (e.g., 'Audit-Ready Commands' duplicates CLI examples, 'When to Use' section explains obvious use cases). The parameter table and CLI examples are well-structured but could be tightened. | 2 / 3 |
Actionability | Provides fully executable CLI commands with concrete examples for both platforms, single and multi-gene modes, and clustering. Parameter table is complete with types and defaults. Commands are copy-paste ready. | 3 / 3 |
Workflow Clarity | Clear 6-step workflow with platform auto-detection logic, explicit validation step (step 3), and a well-structured fallback template for error recovery. The stress-case checklist adds validation checkpoints for complex requests. | 3 / 3 |
Progressive Disclosure | Good structure with quick start at top, detailed CLI usage in middle, and reference to external file (references/parameters.md) for full parameter documentation. Content is appropriately split between overview and details. | 3 / 3 |
Total | 11 / 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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