sin

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 the input unit (radians), which is useful context, but fails to describe key behavioral traits: it doesn't specify the output format (e.g., numeric value), error handling (e.g., for invalid inputs), or mathematical constraints (e.g., domain or precision). For a mathematical tool with zero annotation coverage, this is a significant gap.

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 purpose and key constraint (radians input). There is no wasted language or redundancy, 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 simplicity (one parameter, no annotations, no output schema), the description is incomplete. It covers the basic purpose and input unit but lacks details on output (e.g., numeric result), behavioral aspects (e.g., error handling), and usage relative to siblings. For a mathematical function, more context on expected behavior and alternatives would enhance completeness.

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 schema description coverage is 0%, so the schema provides no parameter details. The description adds some semantics by specifying that the 'angle' parameter is in radians, which clarifies the input unit. However, it doesn't explain the parameter's name, expected range, or format beyond this, leaving gaps in understanding. With one parameter and partial compensation, a baseline 3 is appropriate.

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: '计算角度的正弦值' (calculates the sine of an angle). It specifies the verb (calculate) and resource (sine value), and distinguishes it from siblings like 'cos' or 'tan' by focusing on sine. However, it doesn't explicitly differentiate from all siblings (e.g., 'sinh' for hyperbolic sine), so it's not a perfect 5.

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 notes that the input is in radians ('输入为弧度'), which is essential context for correct use. However, it doesn't specify when to use this tool versus alternatives (e.g., 'sinh' for hyperbolic sine, 'asin' for arcsine, or 'degToRad' for conversion), nor does it mention prerequisites or exclusions. This lack of comparative guidance limits its helpfulness.

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