pseudotime-trajectory-viz
Visualize single-cell developmental trajectories (pseudotime) to show how cells differentiate from stem cells to mature cells. Includes trajectory inference, pseudotime calculation, and publication-ready visualizations.
Install with Tessl CLI
npx tessl i github:aipoch/medical-research-skills --skill pseudotime-trajectory-viz72
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
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 demonstrates strong specificity and distinctiveness within the single-cell biology domain, clearly articulating concrete analytical capabilities. However, it lacks an explicit 'Use when...' clause that would help Claude know exactly when to select this skill, and could benefit from additional natural trigger terms that users might employ when requesting this type of analysis.
Suggestions
Add a 'Use when...' clause with explicit triggers like 'Use when analyzing cell differentiation, lineage trajectories, or when the user mentions pseudotime, trajectory analysis, or developmental paths'
Include common tool names and variations users might mention: 'Monocle', 'Slingshot', 'diffusion pseudotime', 'lineage tracing', 'fate mapping'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'trajectory inference', 'pseudotime calculation', and 'publication-ready visualizations'. Also specifies the biological context of 'cells differentiate from stem cells to mature cells'. | 3 / 3 |
Completeness | Clearly answers 'what' with specific capabilities, but lacks an explicit 'Use when...' clause or equivalent trigger guidance. The 'when' is only implied through the domain description. | 2 / 3 |
Trigger Term Quality | Includes domain-specific terms like 'single-cell', 'pseudotime', 'trajectory', 'developmental trajectories', but missing common variations users might say like 'lineage tracing', 'differentiation analysis', 'Monocle', 'Slingshot', or file formats. | 2 / 3 |
Distinctiveness Conflict Risk | Highly specialized niche in single-cell developmental biology with distinct terminology ('pseudotime', 'trajectory inference', 'stem cells to mature cells') that is unlikely to conflict with other skills. | 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 strong actionable guidance with executable CLI examples and clear parameter documentation. However, it suffers from verbosity with unnecessary boilerplate sections (Risk Assessment, Security Checklist, Lifecycle Status) that don't add value for Claude. The workflow could benefit from explicit validation checkpoints integrated into the analysis process.
Suggestions
Remove boilerplate sections (Risk Assessment, Security Checklist, Evaluation Criteria, Lifecycle Status, Prerequisites) that don't provide actionable guidance for trajectory analysis
Integrate validation steps directly into the workflow, e.g., 'After running trajectory inference, validate with: check marker gene expression patterns match expected biology'
Move detailed method descriptions and references to a separate METHODS.md file, keeping only brief summaries in the main skill
Add a troubleshooting section with common errors and fixes instead of generic test case placeholders
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill contains significant padding including boilerplate sections (Risk Assessment, Security Checklist, Evaluation Criteria, Lifecycle Status) that add little value. The core technical content is reasonably efficient, but the document could be 40% shorter without losing actionable information. | 2 / 3 |
Actionability | Provides fully executable CLI commands with clear parameter documentation, concrete input/output format specifications, and a complete preprocessing workflow example in Python. The usage examples are copy-paste ready. | 3 / 3 |
Workflow Clarity | The Example Workflow section shows preprocessing steps, but lacks explicit validation checkpoints. The Safety & Best Practices section mentions validation but doesn't integrate it into a clear step-by-step workflow with feedback loops for error recovery. | 2 / 3 |
Progressive Disclosure | Content is reasonably organized with clear sections, but everything is in one monolithic file. The detailed method descriptions, references, and boilerplate sections could be split into separate files. No external file references are provided for advanced topics. | 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.