matplotlib
Low-level plotting library for full customization. Use when you need fine-grained control over every plot element, creating novel plot types, or integrating with specific scientific workflows. Export to PNG/PDF/SVG for publication. For quick statistical plots use seaborn; for interactive plots use plotly; for publication-ready multi-panel figures with journal styling, use scientific-visualization.
78
70%
Does it follow best practices?
Impact
94%
1.06xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./scientific-skills/matplotlib/SKILL.mdQuality
Discovery
89%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 skill description that excels at disambiguation by explicitly contrasting itself with related skills (seaborn, plotly, scientific-visualization). The 'Use when' clause is well-constructed with clear trigger conditions. The main weakness is that the specific capabilities could be more concrete — listing actual plot types or specific customization actions rather than abstract phrases like 'fine-grained control over every plot element'.
Suggestions
Add more concrete action verbs and specific capabilities, e.g., 'Create custom scatter plots, bar charts, heatmaps, annotate axes, configure tick marks, build composite figures' instead of the abstract 'fine-grained control over every plot element'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Describes the domain (low-level plotting) and some actions (full customization, creating novel plot types, export to PNG/PDF/SVG), but doesn't list multiple concrete specific actions like 'create bar charts, scatter plots, heatmaps, annotate axes'. The actions remain somewhat abstract ('fine-grained control over every plot element'). | 2 / 3 |
Completeness | Clearly answers both 'what' (low-level plotting library for full customization, export to PNG/PDF/SVG) and 'when' ('Use when you need fine-grained control over every plot element, creating novel plot types, or integrating with specific scientific workflows'). Also explicitly states when NOT to use it, which strengthens the 'when' guidance. | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'plotting', 'plot', 'customization', 'PNG', 'PDF', 'SVG', 'publication', 'scientific workflows', 'multi-panel figures'. Also references competing tools (seaborn, plotly, scientific-visualization) which helps with disambiguation. Users asking about matplotlib-style plotting would naturally use these terms. | 3 / 3 |
Distinctiveness Conflict Risk | Excellent distinctiveness — explicitly differentiates itself from seaborn (quick statistical plots), plotly (interactive plots), and scientific-visualization (publication-ready multi-panel figures with journal styling). This clear boundary-setting makes it very unlikely to conflict with related visualization skills. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
50%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is comprehensive and highly actionable with excellent executable code examples, but it is far too verbose for a Claude skill. It explains many concepts Claude already knows (matplotlib hierarchy, what different plot types are for, basic interface differences) and includes sections like 'When to Use This Skill' and 'Additional Resources' that waste tokens. The content would benefit from aggressive trimming to focus only on project-specific conventions, preferred patterns, and non-obvious guidance.
Suggestions
Remove the 'Core Concepts' hierarchy explanation, 'When to Use This Skill' section, 'Integration with Other Tools', and 'Additional Resources' - Claude already knows all of this.
Trim the plot types section to just the code snippets without descriptions of what each plot type is for (e.g., remove 'Time series, continuous data, trends' annotations).
Move the detailed plot type examples and styling options entirely to the referenced files rather than partially duplicating them inline.
Condense the 'Best Practices' section to a compact checklist format rather than expanded subsections with explanations.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is extremely verbose, explaining concepts Claude already knows well (the matplotlib hierarchy, what a Figure/Axes/Artist is, what line plots vs scatter plots are, two interfaces). The 'When to Use This Skill' section lists obvious use cases. The 'Core Concepts' section explains basic matplotlib architecture that Claude has extensive training on. The 'Integration with Other Tools' and 'Additional Resources' sections add little value. | 1 / 3 |
Actionability | The skill provides fully executable, copy-paste ready code examples throughout - from basic plots to subplots, 3D plots, saving figures, and styling. Code examples are complete with imports and realistic parameters. | 3 / 3 |
Workflow Clarity | The workflows are presented as numbered sections with clear code, but there are no validation checkpoints or feedback loops. For a plotting library this is less critical than for destructive operations, but the skill doesn't address verifying output quality or handling common errors in the workflow itself. | 2 / 3 |
Progressive Disclosure | The skill references external files (references/plot_types.md, references/styling_guide.md, etc.) which is good progressive disclosure, but the main file itself is a monolithic wall of content (~300 lines) with extensive inline material that could be split out. The detailed plot type catalog and styling options could live in the referenced files rather than being partially duplicated here. | 2 / 3 |
Total | 8 / 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 |
|---|---|---|
metadata_version | 'metadata.version' is missing | Warning |
Total | 10 / 11 Passed | |
- Repository
- K-Dense-AI/claude-scientific-skills
- Commit
b58ad7e
- Reviewed
Table of Contents
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