cos_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 but does not mention any behavioral traits such as input validation (e.g., handling of non-numeric inputs), error handling, performance characteristics, or output format. For a tool with no annotations, 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: a single sentence that directly states the tool's function, followed by domain and category in parentheses. There is no wasted text, and every part contributes to understanding the tool's purpose efficiently.

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 simplicity (one parameter, no output schema, no annotations), the description is incomplete. It lacks information on output (e.g., returns a numeric value), error conditions, and behavioral context. While concise, it does not provide enough detail for an agent to fully understand how to invoke and interpret results without additional assumptions.

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, with one parameter 'angle_degrees' of type 'number'. The description adds minimal semantics by specifying 'an angle in degrees', which clarifies the unit beyond the parameter name. However, it does not provide details on allowed ranges, special values, or examples, leaving the schema to carry most of the parameter documentation.

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 cosine of an angle in degrees.' It specifies the verb ('calculate'), resource ('cosine'), and domain ('trigonometry, Category: basic_functions'), making the intent unambiguous. However, it does not explicitly differentiate from sibling tools like 'cos' (which likely calculates cosine in radians) or 'cos_series', so it misses full sibling distinction.

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 no guidance on when to use this tool versus alternatives. It mentions the domain and category, but does not specify when to choose it over similar tools (e.g., 'cos' for radians, 'cos_series' for series approximation) or any prerequisites. This lack of comparative context leaves usage decisions unclear.

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