pseudotime-trajectory-viz
Visualize single-cell developmental trajectories and cellular differentiation processes using pseudotime analysis on AnnData (.h5ad) files.
78
73%
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/pseudotime-trajectory-viz/SKILL.mdQuality
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 well-crafted, domain-specific description with excellent specificity and trigger terms for the bioinformatics audience. The main weakness is the absence of an explicit 'Use when...' clause, which would help Claude know exactly when to select this skill. The technical terminology is appropriate for the target users but the description would benefit from explicit trigger guidance.
Suggestions
Add a 'Use when...' clause with trigger terms like 'Use when analyzing single-cell RNA-seq data, trajectory inference, pseudotime ordering, or working with .h5ad/AnnData files'
Consider adding common variations users might say, such as 'scRNA-seq', 'trajectory analysis', 'lineage tracing', or 'Scanpy'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists specific concrete actions: 'Visualize single-cell developmental trajectories', 'cellular differentiation processes', 'pseudotime analysis', and specifies the file format (.h5ad). Multiple domain-specific capabilities are clearly stated. | 3 / 3 |
Completeness | Clearly answers 'what does this do' (visualize trajectories, differentiation, pseudotime analysis on AnnData files), 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 excellent natural keywords users in this domain would use: 'single-cell', 'developmental trajectories', 'cellular differentiation', 'pseudotime analysis', 'AnnData', '.h5ad'. These are the exact terms bioinformaticians would naturally mention. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche in single-cell bioinformatics. The combination of 'pseudotime analysis', 'AnnData', and '.h5ad' creates a very specific domain that is unlikely to conflict with other skills. | 3 / 3 |
Total | 11 / 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 excellent parameter documentation and concrete CLI examples, but suffers from a generic workflow section that doesn't reflect the actual pseudotime analysis process. The content is moderately verbose with template sections that could be externalized, and the workflow lacks the specific biological validation steps critical for trajectory inference.
Suggestions
Replace the generic workflow section with specific pseudotime analysis steps: load data → compute neighbors → run trajectory inference → calculate pseudotime → validate with marker genes → generate plots
Add explicit validation checkpoints for biological correctness, such as verifying root cell selection and checking marker gene expression along trajectories
Move the response template and fallback template to a separate reference file to reduce inline verbosity
Add a brief comparison of when to use diffusion vs PAGA methods to help users select the appropriate approach
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill contains some unnecessary verbosity, particularly in the workflow section which is generic rather than specific to pseudotime analysis. The response template and fallback template sections add bulk that could be condensed or referenced externally. | 2 / 3 |
Actionability | Provides fully executable CLI commands with clear parameter documentation, concrete input/output file structures, and specific examples for different use cases. The parameter table and usage examples are copy-paste ready. | 3 / 3 |
Workflow Clarity | The workflow section is surprisingly generic and doesn't describe the actual pseudotime analysis steps. While error handling includes validation checkpoints, the core workflow lacks specific trajectory inference steps and validation of biological results. | 2 / 3 |
Progressive Disclosure | Content is reasonably organized with clear sections, but everything is inline in one file. The response template and fallback template sections could be referenced externally. No links to detailed documentation for advanced features like PAGA vs diffusion method selection. | 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
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