Turf-MCP

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden and does well by disclosing: the return format (JSON string with boolean value), error conditions (JavaScript execution failure, timeout, malformed input), coordinate system requirements (WGS84 with [longitude, latitude] order), and implementation dependencies (Turf.js and Node.js). It doesn't mention performance characteristics or rate limits, but provides substantial behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (Args, Returns, Raises, Example, Notes) and front-loads the core purpose. While comprehensive, some sections could be more concise (the example includes full import statements and async code). Overall, most sentences earn their place by providing essential information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (geospatial boolean operation), the description provides complete context: purpose, detailed parameter semantics, return format, error conditions, examples, and implementation notes. With an output schema present, the description appropriately focuses on explaining the boolean relationship rather than repeating return value structure. It covers all essential aspects for correct tool invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage (schema only shows parameter names and types as strings), the description fully compensates by providing detailed parameter documentation: data types (JSON strings), formats (valid GeoJSON objects), examples, and specific requirements (must be valid JSON strings). This adds significant value beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with specific verbs and resources: '检查两个几何图形是否相交' (checks if two geometries intersect) and elaborates on the specific type of intersection ('交叉但不相交于边界点' - crossing but not intersecting at boundary points). It distinguishes from siblings like 'booleans_booleanContains' and 'booleans_booleanWithin' by specifying the exact topological relationship being tested.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context through the definition of 'booleanCrosses' and notes about boundary contact not counting as crossing, but doesn't explicitly state when to use this tool versus alternatives like 'booleans_booleanOverlap' or 'booleans_booleanIntersects'. The sibling tool list shows many boolean operations, but no explicit guidance is provided for choosing among them.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.