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: it discloses that the tool returns a bounding box array, specifies coordinate system (WGS84), format requirements (JSON string), and implementation dependencies (Turf.js, Node.js). It also mentions error conditions (JavaScript execution failures, timeouts, invalid data). However, it doesn't cover performance characteristics like computational complexity.

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-loaded purpose statement. It's appropriately sized for a single-parameter tool with detailed requirements. The only minor inefficiency is the inclusion of Python example code in what appears to be a JavaScript/Node.js context.

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?

For a tool with 1 parameter, no annotations, 0% schema coverage, but with output schema (implied by Returns section), the description is complete: it covers purpose, parameter details, return format, error conditions, examples, and implementation notes. The output schema equivalent in the Returns section eliminates the need to describe return values in the main description.

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?

The input schema has 0% description coverage (just 'geojson' as a string type), but the description comprehensively documents the single parameter: it explains geojson must be a valid JSON string, specifies the coordinate system (WGS84), provides format details (any valid GeoJSON), and gives a concrete example. This fully compensates for the schema's lack of documentation.

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: '计算地理对象的边界范围' (calculates the bounding box of geographic objects). It specifies the verb ('计算' - calculate) and resource ('地理对象的边界范围' - bounding box of geographic objects), and distinguishes itself from sibling tools like 'measurement_bboxPolygon' by focusing on coordinate arrays rather than polygon representations.

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 provides clear context for when to use this tool: for calculating bounding boxes from GeoJSON objects. It doesn't explicitly state when not to use it or name alternatives, but the sibling list shows 'measurement_bboxPolygon' as a potential alternative for polygon-based bounding boxes, which is implied but not explicitly contrasted.

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