catenary_curve

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 tool calculates parameters and properties but does not describe what specific parameters or properties are returned, whether the calculation is deterministic, any error handling, or performance characteristics. For a mathematical 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 concise and front-loaded, consisting of a single sentence that directly states the tool's purpose. The domain/category information is included parenthetically, adding context without unnecessary elaboration. There is no wasted verbiage, making it efficient for quick understanding.

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 complexity of a mathematical calculation tool with 2 undocumented parameters, no annotations, and no output schema, the description is insufficient. It does not explain what the tool returns (e.g., curve length, sag, tension), how results are formatted, or any mathematical assumptions. This leaves the agent without enough information to use the tool effectively in context.

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 two parameters ('a' and 'x') with 0% description coverage, meaning the schema provides no semantic information. The description does not explain what 'a' and 'x' represent (e.g., 'a' might be the scaling parameter, 'x' the independent variable), their units, or valid ranges. This fails to compensate for the lack of schema documentation, leaving parameters largely undefined.

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 catenary curve parameters and properties.' It specifies a verb ('calculate') and resource ('catenary curve parameters and properties'), and includes domain/category context ('trigonometry, hyperbolic'). However, it does not explicitly distinguish this tool from sibling tools like 'hyperbolic_functions' or 'verify_hyperbolic_identity', which might also involve hyperbolic functions or curves.

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 lacks any mention of prerequisites, typical use cases, or comparisons to sibling tools (e.g., 'hyperbolic_functions' or other curve-related tools). The domain/category tags ('trigonometry, hyperbolic') imply a context but do not offer explicit usage instructions.

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