asech

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

No annotations are provided, so the description carries the full burden. It mentions 'domain validation', which hints at input constraints (likely x in (0,1] for asech), but does not detail error handling, output format, or computational behavior. This adds some context but leaves gaps in behavioral understanding for a mathematical function tool.

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: one sentence with no wasted words. It front-loads the core action ('Calculate inverse hyperbolic secant') and adds clarifying context ('with domain validation'). This is efficient and well-structured for a simple mathematical tool.

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-parameter mathematical function) and no output schema, the description is minimally adequate. It covers the operation and hints at validation, but lacks details on return values, error cases, or examples. With no annotations, it should provide more behavioral context to be fully complete for reliable agent use.

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 (x) with 0% description coverage. The description does not explain what 'x' represents (e.g., a real number in the domain of asech) or provide examples. Since schema coverage is low, the description should compensate more; it only implies domain validation without parameter specifics, meeting the baseline but not adding significant value.

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 inverse hyperbolic secant with domain validation.' It specifies the mathematical operation (inverse hyperbolic secant) and adds domain validation as a key feature. However, it does not explicitly differentiate from sibling tools like 'sech' (direct hyperbolic secant) or other inverse hyperbolic functions in the list, which would be needed for a score of 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 no guidance on when to use this tool versus alternatives. It mentions the domain (trigonometry) and category (inverse_hyperbolic), but does not specify use cases, prerequisites, or compare it to related tools like 'acosh' or 'asec'. Without explicit when-to-use instructions, the agent must infer usage from context alone.

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