atan_degrees

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

No annotations are provided, so the description carries full burden. It states the tool calculates arctangent in degrees, which implies a mathematical computation with no side effects. However, it doesn't mention any behavioral aspects like error handling (e.g., for invalid inputs), performance characteristics, or whether the input 'value' represents a ratio (y/x) for single-argument arctangent. The domain/category tags add some context but don't fully describe behavior.

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 core functionality. The parenthetical domain/category information is brief and relevant. There's no wasted verbiage or unnecessary elaboration, making it efficient for an AI agent to parse.

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 (single mathematical function), no annotations, no output schema, and minimal parameters, the description is somewhat complete but has gaps. It specifies what the tool does and the output unit, but doesn't explain parameter meaning, error conditions, or differentiation from similar tools. For a basic mathematical function, this might be minimally adequate, but more context would improve agent understanding.

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 1 parameter with 0% description coverage. The tool description doesn't explain what the 'value' parameter represents (e.g., that it's the tangent ratio y/x for single-argument arctangent). Since schema coverage is 0%, the description should compensate but only adds minimal context through the domain/category. This meets the baseline for a single-parameter tool but lacks detailed semantic clarification.

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 arctangent with result in degrees.' It specifies both the mathematical function (arctangent) and the output unit (degrees), which is more specific than just the tool name. However, it doesn't explicitly differentiate from its sibling 'atan' (which likely returns radians) or 'atan2_degrees', leaving some ambiguity about when to choose this exact tool.

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 usage guidance. It mentions 'Domain: trigonometry, Category: inverse_functions' which gives high-level context but doesn't specify when to use this tool versus alternatives like 'atan' (radians output) or 'atan2_degrees' (two-argument version). No explicit when-to-use or when-not-to-use instructions are provided.

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