arcgis-smart-mapping
Auto-generate renderers, calculate statistics, and create data-driven visualizations. Use for class breaks, unique values, heatmaps, dot density, relationship maps, and getting histogram/summary statistics.
79
74%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./contexts/4.34/skills/arcgis-smart-mapping/SKILL.mdQuality
Discovery
92%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 description that lists specific concrete actions and includes domain-specific trigger terms that GIS/mapping users would naturally use. The 'Use for...' clause effectively communicates when to select this skill. The main weakness is potential overlap with general visualization or statistics skills due to some broader terms, though the GIS-specific terminology helps mitigate this.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'auto-generate renderers', 'calculate statistics', 'create data-driven visualizations', plus specific types like 'class breaks, unique values, heatmaps, dot density, relationship maps, histogram/summary statistics'. | 3 / 3 |
Completeness | Clearly answers both what ('auto-generate renderers, calculate statistics, create data-driven visualizations') and when ('Use for class breaks, unique values, heatmaps, dot density, relationship maps, and getting histogram/summary statistics') with explicit trigger scenarios. | 3 / 3 |
Trigger Term Quality | Includes strong natural keywords users would say: 'renderers', 'class breaks', 'unique values', 'heatmaps', 'dot density', 'relationship maps', 'histogram', 'summary statistics', 'visualizations'. These are domain-specific terms a GIS/mapping user would naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | The terms 'visualizations', 'statistics', and 'heatmaps' could overlap with general data visualization or statistics skills. However, the GIS-specific terms like 'renderers', 'class breaks', 'dot density', and 'unique values' help narrow the niche. It's somewhat specific but 'visualizations' and 'statistics' are broad enough to cause potential conflicts. | 2 / 3 |
Total | 11 / 12 Passed |
Implementation
57%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 code examples covering the full ArcGIS smart mapping API surface. However, it suffers from being a monolithic reference document (~400+ lines) that would benefit greatly from progressive disclosure—splitting detailed renderer types, statistics functions, and raster renderers into separate files. Workflow clarity could be improved by integrating validation steps (layer loading checks, error handling) directly into the workflow patterns.
Suggestions
Split content into separate files (e.g., RENDERERS.md, STATISTICS.md, RASTER.md, SYMBOLOGY.md) and make SKILL.md a concise overview with links to each, reducing the main file to under 100 lines.
Remove brief prose descriptions before code blocks (e.g., 'Creates a renderer with color gradient based on numeric values') since the code and section headers already convey this information.
Add explicit validation/error handling steps to the 'Complete Smart Mapping Workflow' section, such as checking layer.loaded, try/catch around async calls, and verifying renderer application.
Consolidate the 'Common Pitfalls' into the workflow section as inline validation checkpoints rather than listing them separately at the end.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is quite long (~400+ lines) and includes many renderer types that could be split into separate reference files. Brief descriptions like 'Creates a renderer with color gradient based on numeric values' are unnecessary given Claude's intelligence, but the code examples themselves are lean and well-commented. | 2 / 3 |
Actionability | Every section provides fully executable JavaScript code with proper imports, destructured return values, and inline comments showing parameter options. The code is copy-paste ready and covers all major smart mapping use cases with concrete examples. | 3 / 3 |
Workflow Clarity | The 'Complete Smart Mapping Workflow' section shows a numbered sequence but lacks validation checkpoints (e.g., checking if the layer loaded successfully, verifying renderer was applied correctly). The 'Common Pitfalls' section partially compensates but doesn't integrate validation into the workflow steps themselves. | 2 / 3 |
Progressive Disclosure | This is a monolithic wall of content with no references to external files for detailed sections. The renderer creators, statistics functions, raster renderers, and symbology sections could each be separate reference files, with SKILL.md serving as a concise overview with links. | 1 / 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 |
|---|---|---|
skill_md_line_count | SKILL.md is long (694 lines); consider splitting into references/ and linking | Warning |
Total | 10 / 11 Passed | |
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