radians_to_degrees

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'high precision,' which adds some context about output quality, but fails to describe other critical behaviors such as error handling (e.g., for invalid inputs), performance characteristics, or the format of the result. For a tool with zero annotation coverage, this is a significant gap in transparency.

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 extremely concise and front-loaded: the first sentence directly states the tool's purpose, and the second provides domain/category tags without unnecessary elaboration. Every word serves a clear purpose, making it efficient and easy to parse for an AI agent.

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 low complexity (one input, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose and domain but lacks details on output format, error conditions, or precision specifics. While the simplicity of the tool means extensive documentation isn't critical, the absence of any behavioral or output information keeps the completeness at a baseline level.

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, but the tool has only one parameter ('radians'), which is self-explanatory given the tool's name and purpose. The description does not add any parameter-specific details beyond what is implied by the context, such as expected units or valid ranges. With a single, straightforward parameter, the baseline score of 3 is appropriate, as the schema's lack of description is mitigated by the parameter's simplicity.

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: 'Convert radians to degrees with high precision.' It specifies the verb ('Convert'), resource ('radians to degrees'), and quality ('high precision'), making the function unambiguous. However, it does not explicitly differentiate from sibling tools like 'degrees_to_radians' or 'convert_angle', which would be needed for a perfect score.

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 minimal guidance with the domain and category tags ('Domain: trigonometry, Category: angle_conversion'), which imply usage in trigonometric contexts. However, it lacks explicit instructions on when to use this tool versus alternatives like 'degrees_to_radians' or 'convert_angle', and offers no exclusions or prerequisites. This leaves the agent with insufficient direction for optimal tool selection.

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