unit_conversion_degreesToRadians

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 conversion formula, dependencies on Turf.js and Node.js, return format details, and error conditions (JavaScript execution failures, timeouts, input format errors). It doesn't mention performance characteristics or rate limits, but provides substantial behavioral context beyond basic functionality.

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 with the core purpose. Some sections like the Python example could be more concise for an MCP context, but overall the information density is high with minimal waste.

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 single-parameter mathematical conversion tool with no annotations and no output schema, the description provides excellent completeness: clear purpose, detailed parameter documentation, explicit return format specification, error conditions, usage examples, mathematical formula, and implementation dependencies. Nothing essential appears to be missing for this type of tool.

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 'degrees' as a number type), the description fully compensates by providing detailed parameter documentation: type (float), description, example value (180.0), and context about what the parameter represents. This adds significant value beyond the minimal schema information.

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 specific verb ('将角度转换为弧度' - convert degrees to radians) and resource (angle values). It distinguishes from sibling tools like 'unit_conversion_radiansToDegrees' by specifying the exact conversion direction. The purpose is unambiguous and specific.

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 'Notes' section ('常用于数学计算和三角函数' - commonly used in mathematical calculations and trigonometric functions), but doesn't explicitly state when to use this tool versus alternatives like 'unit_conversion_radiansToDegrees' or other unit conversion tools. No explicit when-not-to-use guidance or prerequisites are provided.

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