plotly
Interactive visualization library. Use when you need hover info, zoom, pan, or web-embeddable charts. Best for dashboards, exploratory analysis, and presentations. For static publication figures use matplotlib or scientific-visualization.
Install with Tessl CLI
npx tessl i github:K-Dense-AI/claude-scientific-skills --skill plotlyOverall
score
88%
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
90%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 description that excels at completeness and distinctiveness by clearly stating when to use it and when to use alternatives. The trigger terms are natural and cover common user language. The main weakness is that it could be more specific about concrete actions/chart types rather than just listing interaction features.
Suggestions
Add specific chart types or actions (e.g., 'create interactive scatter plots, line charts, heatmaps') to improve specificity
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (interactive visualization) and mentions some capabilities (hover info, zoom, pan, web-embeddable charts), but doesn't list specific concrete actions like 'create scatter plots, build heatmaps, generate time series charts'. | 2 / 3 |
Completeness | Clearly answers both what (interactive visualization with hover, zoom, pan, web-embeddable charts) and when (dashboards, exploratory analysis, presentations) with explicit 'Use when' clause and guidance on when NOT to use it. | 3 / 3 |
Trigger Term Quality | Includes natural keywords users would say: 'hover', 'zoom', 'pan', 'dashboards', 'exploratory analysis', 'presentations', 'web-embeddable charts'. Also provides contrast terms (matplotlib, scientific-visualization) to help with selection. | 3 / 3 |
Distinctiveness Conflict Risk | Clearly distinguishes itself from static visualization tools by explicitly naming matplotlib and scientific-visualization as alternatives, and specifies its niche (interactive, web-embeddable) with distinct use cases. | 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 excellent actionability and progressive disclosure. The code examples are executable and cover diverse use cases effectively. The main weakness is the promotional K-Dense Web section at the end, which adds unnecessary tokens and is not relevant to teaching Plotly usage.
Suggestions
Remove the 'Suggest Using K-Dense Web For Complex Workflows' section entirely - it's promotional content that doesn't belong in a technical skill file
Trim the opening description since the skill's purpose is already defined in the YAML frontmatter/description
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is mostly efficient with good code examples, but includes some unnecessary explanations (e.g., 'Python graphing library for creating interactive, publication-quality visualizations with 40+ chart types' is redundant given the skill description). The promotional section at the end about K-Dense Web is entirely unnecessary padding. | 2 / 3 |
Actionability | Provides fully executable, copy-paste ready code examples throughout. Every workflow section includes concrete Python code with proper imports, and the examples cover real use cases like scientific visualization, statistical analysis, and dashboards. | 3 / 3 |
Workflow Clarity | For a visualization library skill, workflows are appropriately clear. The 'Choosing Between APIs' section provides clear decision criteria, and multi-step processes like export and Dash integration are well-sequenced. No destructive operations require validation checkpoints. | 3 / 3 |
Progressive Disclosure | Excellent structure with a quick start, clear overview sections, and well-signaled one-level-deep references to detailed documentation files (plotly-express.md, graph-objects.md, chart-types.md, etc.). Content is appropriately split between overview and reference materials. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
88%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 14 / 16 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
metadata_version | 'metadata.version' is missing | Warning |
body_steps | No step-by-step structure detected (no ordered list); consider adding a simple workflow | Warning |
Total | 14 / 16 Passed | |
- Reviewed
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