Content
42%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The skill excels at actionability with comprehensive, executable YAML examples for every canvas component type, making it a strong reference. However, it is severely undermined by its length and monolithic structure—it reads like a full reference manual crammed into a single file, wasting context window tokens on repetitive patterns and explanations Claude doesn't need. Splitting component references into separate files and trimming introductory/explanatory content would dramatically improve its effectiveness.
Suggestions
Extract the detailed component type references (line_chart, bar_chart, stacked_bar, etc.) into a separate COMPONENTS_REFERENCE.md file, keeping only a summary table with one-line descriptions and links in the main SKILL.md.
Remove the introductory section explaining what canvas dashboards are and when to use them—Claude can infer this from the examples. Cut the field type definitions (nominal, temporal, quantitative) as these are standard concepts.
Add validation/debugging guidance: how to verify a canvas renders correctly, common YAML errors, and what to check when a component shows no data.
Reduce redundant examples—most chart types share the same x/y/color pattern. Show one canonical chart example in detail, then use minimal diffs for variants.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is extremely verbose at ~600+ lines. It explains concepts Claude already knows (what canvas dashboards are, how they differ from explore dashboards, what nominal/temporal/quantitative types mean). The introduction section, 'when to use' bullets, and field type definitions are unnecessary padding. Nearly every component type includes multiple full YAML examples when one would suffice, and many patterns are repetitive across chart types. | 1 / 3 |
Actionability | The skill provides fully executable, copy-paste-ready YAML configurations for every component type. The metrics_sql examples, Vega-Lite specs, and complete dashboard example are concrete and specific. Field names, property values, and configuration options are all explicitly documented with working examples. | 3 / 3 |
Workflow Clarity | The 'Dashboard Composition Best Practices' section provides a clear recommended sequence for building dashboards (Row 1 context, Row 2 KPIs, Row 3 analysis, etc.), and chart type selection guidance is helpful. However, there are no validation checkpoints, no error recovery steps, and no guidance on how to verify a canvas dashboard renders correctly or debug common issues. | 2 / 3 |
Progressive Disclosure | This is a monolithic wall of text with no references to external files. The detailed component reference for every chart type (line, bar, stacked bar, area, donut, heatmap, combo, scatter, funnel, pivot, table, image, custom chart) should be split into separate reference files. The SKILL.md should be a concise overview with links to component-specific documentation. | 1 / 3 |
Total | 7 / 12 Passed |