visualization-best-practices
Visualization Best Practices - Auto-activating skill for Data Analytics. Triggers on: visualization best practices, visualization best practices Part of the Data Analytics skill category.
32
0%
Does it follow best practices?
Impact
92%
0.98xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./planned-skills/generated/12-data-analytics/visualization-best-practices/SKILL.mdQuality
Discovery
0%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 is critically underdeveloped and fails on all dimensions. It provides no concrete actions, no meaningful trigger terms, no explicit usage guidance, and nothing to distinguish it from other analytics skills. The repetition of 'visualization best practices' as the only trigger term suggests this may be auto-generated boilerplate rather than a thoughtfully crafted description.
Suggestions
Add specific concrete actions the skill performs, such as 'Recommends chart types based on data structure, applies accessible color palettes, formats axis labels and legends, optimizes layouts for readability'
Include a 'Use when...' clause with natural trigger scenarios like 'Use when creating charts, graphs, dashboards, or when the user asks about chart formatting, color choices, or data presentation'
Add diverse trigger terms users would naturally say: 'chart', 'graph', 'plot', 'dashboard', 'data viz', 'bar chart', 'line graph', 'scatter plot', 'color scheme', 'legend formatting'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description uses vague language like 'best practices' without listing any concrete actions. It doesn't specify what the skill actually does - no mention of creating charts, choosing color schemes, formatting axes, or any other specific visualization tasks. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond the vague 'best practices' and has no explicit 'when to use' guidance. The 'Triggers on' section just repeats the skill name rather than providing meaningful trigger scenarios. | 1 / 3 |
Trigger Term Quality | The only trigger terms listed are 'visualization best practices' repeated twice. This is overly generic and misses natural user phrases like 'chart', 'graph', 'plot', 'dashboard', 'data viz', or specific chart types users might mention. | 1 / 3 |
Distinctiveness Conflict Risk | The description is extremely generic and would likely conflict with any other data analytics or visualization-related skills. 'Data Analytics skill category' provides no distinguishing characteristics from other analytics skills. | 1 / 3 |
Total | 4 / 12 Passed |
Implementation
0%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill content is entirely meta-description with no substantive guidance on visualization best practices. It describes what the skill should do without actually doing it - there are no chart type recommendations, color palette guidance, accessibility considerations, or any concrete visualization techniques. The content is essentially a placeholder that provides zero value to Claude.
Suggestions
Add concrete visualization best practices content: chart type selection guidelines (when to use bar vs line vs scatter), color accessibility rules, data-ink ratio principles, and labeling standards
Include executable code examples showing how to create effective visualizations with common libraries (matplotlib, seaborn, plotly) with before/after comparisons
Provide a decision tree or checklist for choosing appropriate visualization types based on data characteristics (categorical vs continuous, comparison vs distribution vs relationship)
Add specific anti-patterns to avoid with visual examples or descriptions (e.g., 3D pie charts, truncated axes, rainbow color scales)
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic boilerplate that provides no actual information about visualization best practices. Every section describes what the skill does abstractly rather than providing any concrete guidance. | 1 / 3 |
Actionability | There is zero actionable content - no concrete examples, no code, no specific visualization techniques, no actual best practices. The content only describes that it will provide guidance without actually providing any. | 1 / 3 |
Workflow Clarity | No workflow is defined. The skill claims to provide 'step-by-step guidance' but contains no actual steps, processes, or procedures for creating effective visualizations. | 1 / 3 |
Progressive Disclosure | The content is a monolithic block of meta-description with no actual content to organize. There are no references to detailed materials, examples, or related documentation that would provide real value. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
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- Reviewed
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