is_automorphic_number

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 only states what the tool does (checks automorphicity) but does not describe any behavioral traits such as input constraints (e.g., handling of negative numbers, large integers), performance characteristics, error handling, or output format. This leaves significant gaps for an agent to understand how to invoke it correctly.

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, with the core purpose stated in the first sentence. The additional domain and category information is brief and relevant. There is no wasted verbiage, making it efficient for quick understanding, though it could be slightly more structured with explicit parameter or usage notes.

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 moderate complexity (mathematical check with one parameter), no annotations, no output schema, and low schema description coverage, the description is incomplete. It lacks details on behavioral traits, parameter semantics, and output expectations, which are crucial for an agent to use the tool effectively. The domain/category tags do not compensate for these gaps.

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 with 0% description coverage, so the description must compensate. It implies the parameter 'n' is the number to check, but does not specify any semantics beyond that (e.g., valid ranges, integer type). The description adds minimal value over the schema, as it does not explain parameter meaning or usage, resulting in a baseline score due to the lack of detailed parameter information.

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 with a specific verb ('Check') and resource ('if a number is automorphic'), and includes a precise mathematical definition ('its square ends with the number itself'). It also distinguishes from sibling tools by specifying a unique arithmetic domain and category, unlike generic tools like 'is_prime' or 'is_even'.

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 does not mention any prerequisites, constraints, or sibling tools that might be relevant (e.g., 'automorphic_numbers' for generating such numbers). The domain and category tags are generic and do not offer specific usage instructions.

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