asin_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 mention input constraints (e.g., domain of arcsine: -1 ≤ value ≤ 1), error handling, precision, or performance characteristics. For a mathematical tool with no annotation coverage, this leaves significant gaps in understanding its 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 concise and front-loaded, stating the core functionality in the first phrase. The additional domain/category context is brief and relevant. There is no wasted verbiage, though it could be more informative without sacrificing brevity.

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 mathematical nature, no annotations, 0% schema coverage, and no output schema, the description is incomplete. It lacks details on input constraints, output format, error conditions, and sibling differentiation. While the purpose is clear, the overall context for reliable use is insufficient.

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, documenting only that 'value' is a required number. The description adds no parameter semantics—it does not explain what 'value' represents (e.g., sine ratio), valid ranges, or units. With low schema coverage, the description fails to compensate, leaving the parameter poorly defined.

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 arcsine with result in degrees.' It specifies the mathematical operation (arcsine), the output unit (degrees), and the domain/category (trigonometry, inverse_functions). However, it does not explicitly differentiate from its sibling 'asin' (which likely returns radians), though the '_degrees' suffix implies this.

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 use cases, prerequisites, or comparisons to siblings like 'asin' (radians output) or other inverse trigonometric functions. The agent must infer usage from the name and context alone.

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