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Scored across 113 tools
Each tool has a clearly distinct purpose with no ambiguity. The tools are well-organized into categories (aggregation, booleans, measurement, etc.), and within each category, tools target specific geometric operations or algorithms. Descriptions are detailed and differentiate between similar tools (e.g., DBSCAN vs. K-means clustering, various boolean operations).
Tool names follow a highly consistent snake_case pattern with clear category prefixes (e.g., aggregation_clustersDbscan, booleans_booleanContains, measurement_area). The naming is predictable and readable throughout all 113 tools, with no mixing of conventions or chaotic variations.
With 113 tools, the count is excessive for a single server's scope, even for a comprehensive geospatial library. This many tools can overwhelm agents and make discovery difficult. While the domain (Turf.js geospatial operations) is broad, a more modular approach with fewer, more generalized tools would be more appropriate.
The tool set provides complete coverage of the Turf.js geospatial operations domain. It includes aggregation, boolean operations, measurements, transformations, interpolation, joins, and utilities, with no obvious gaps. The surface supports a wide range of geospatial workflows from basic geometry creation to advanced spatial analysis.