measurement_square

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 implementation details (uses Turf.js library, Node.js environment), error conditions (JavaScript execution failure, timeout, input format errors), and output format specifics. It doesn't mention performance characteristics like rate limits, but covers key behavioral aspects.

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. It could be slightly more concise in the Notes section, but every sentence adds value. The bilingual presentation (Chinese with English code) is efficient for its 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?

Given the tool's moderate complexity (geometric transformation), no annotations, and an output schema present, the description is complete. It explains the transformation logic, input/output formats, dependencies, error conditions, and provides a working example. The output schema existence means return values don't need detailed explanation in the 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?

With 0% schema description coverage (input schema only shows 'bbox' as a string type), the description fully compensates. It provides detailed parameter semantics: format requirements (JSON string), coordinate order [minX, minY, maxX, maxY], coordinate system (WGS84), and examples. This adds substantial value beyond the minimal 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: '计算包含边界框的最小正方形边界框' (calculates the minimum square bounding box containing a given bounding box). It specifies the exact operation (calculate), resource (bounding box), and distinguishes from siblings like 'measurement_bbox' (which likely returns the original bounding box) by focusing on square transformation.

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: when you need a square bounding box from an input bounding box. It doesn't explicitly state when not to use it or name alternatives among siblings, but the specific purpose implies usage scenarios well.

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