atan2_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 states the calculation and output format but does not cover critical behavioral aspects such as error handling (e.g., for x=0, y=0), input constraints (e.g., domain of valid numbers), or performance characteristics. For a mathematical function 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, consisting of a single sentence that directly states the tool's function and output. The domain and category tags are appended efficiently without redundancy. Every word earns its place, making it highly readable and to-the-point.

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 complexity of a mathematical function with two parameters, no annotations, and no output schema, the description is incomplete. It lacks details on parameter meanings, behavioral traits (e.g., edge cases), and output format beyond 'degrees'. For a tool in a server with many siblings, more context is needed to ensure correct usage without ambiguity.

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 two parameters (y and x) with 0% description coverage, meaning the schema provides no semantic information. The description does not explain what y and x represent (e.g., Cartesian coordinates, vector components) or their roles in the calculation (e.g., atan2(y, x) convention). It adds no parameter semantics beyond the bare schema, failing to compensate for the low coverage.

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: 'Calculate two-argument arctangent with result in degrees.' It specifies the verb ('calculate'), resource ('two-argument arctangent'), and output unit ('degrees'), which is specific and unambiguous. However, it does not explicitly differentiate from sibling tools like 'atan' or 'atan2', which likely produce results in radians or have different parameter conventions, so it falls short of 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 implies usage through the domain and category tags ('trigonometry', 'inverse_functions'), suggesting it should be used for trigonometric calculations involving inverse functions. However, it does not provide explicit guidance on when to use this tool versus alternatives like 'atan' (single-argument arctangent) or 'atan2' (likely in radians), nor does it mention any prerequisites or exclusions. The guidance is implied but not detailed.

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