asin

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 'domain validation,' which hints at input constraints (likely for the arcsine function's domain of [-1, 1]), but does not detail what happens on invalid inputs (e.g., error messages, exceptions, or default behaviors). It also omits information about output format, precision, or any side effects. For a mathematical function tool with no annotations, this is insufficient.

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: it states the core purpose in the first phrase and adds context in parentheses. There is no wasted language, and every word contributes to understanding the tool's function and domain. This efficiency makes it easy to parse quickly.

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 complexity (a mathematical function with domain constraints), the lack of annotations, no output schema, and low parameter schema coverage, the description is incomplete. It does not cover behavioral aspects like error handling, output details (e.g., range in radians), or usage distinctions from siblings. While concise, it fails to provide the necessary context for effective tool selection and invocation.

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 one parameter ('value') with 0% description coverage, and the description does not add any semantic details about this parameter. It does not explain what 'value' represents (e.g., a sine ratio between -1 and 1), its expected units (radians vs. degrees), or the implications of domain validation. With low schema coverage and no compensation in the description, this leaves the parameter poorly documented.

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 (inverse sine) with domain validation.' It specifies the verb ('calculate') and resource ('arcsine'), and distinguishes it from siblings like 'asin_degrees' by implying this version uses radians (though not explicitly stated). However, it does not explicitly differentiate from 'asin_degrees' in the description text, which holds it back from 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 provides minimal guidance: it mentions domain validation and categorizes the tool under 'trigonometry' and 'inverse_functions,' which gives some context. However, it does not specify when to use this tool versus alternatives like 'asin_degrees' or 'asinh,' nor does it provide any prerequisites, exclusions, or explicit usage scenarios. 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.