acosh

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

No annotations are provided, so the description carries full burden. It mentions 'domain validation', which is a useful behavioral trait, but doesn't disclose other important aspects like error handling (e.g., what happens if x < 1), performance characteristics, or output format. For a mathematical function tool with no annotations, 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 extremely concise and front-loaded: a single sentence that states the core functionality and key feature (domain validation), followed by a parenthetical category. Every word earns its place with no redundancy or fluff.

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, no output schema, and 0% schema description coverage, the description is incomplete. It doesn't explain what the tool returns, error conditions, or mathematical context beyond the basic operation. For a tool that performs a specific mathematical calculation, more context about behavior and results would be helpful.

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?

Schema description coverage is 0%, so the description must compensate. It mentions 'domain validation' which adds context about the parameter 'x' (likely requiring x ≥ 1 for real results), but doesn't explicitly explain the parameter's role or constraints. The description provides some semantic value beyond the bare schema, but not enough to fully document the single parameter.

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 cosine (area cosine) with domain validation.' It specifies the verb ('calculate'), resource ('inverse hyperbolic cosine'), and includes domain validation as a key feature. However, it doesn't explicitly differentiate from sibling tools like 'acosh' vs 'asinh' or 'atanh', though the category 'inverse_hyperbolic' provides some context.

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 mentions domain validation, which implies the tool handles input validation, but doesn't specify when to use this tool versus alternatives like 'cosh' or other inverse hyperbolic functions. No explicit when/when-not instructions or alternative tool references are provided.

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