nth_perfect_square

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 'Get[s] the nth perfect square' but does not elaborate on behavior such as input validation (e.g., handling negative 'n'), output format (e.g., integer result), error handling, or computational limits. The description is minimal and lacks critical behavioral details needed for safe and effective use.

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: 'Get the nth perfect square (0-indexed).' It wastes no words and directly states the core functionality. The additional context ('Domain: arithmetic, Category: basic_sequences') is brief and relevant, making every sentence earn its place without redundancy.

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 simplicity (one parameter, no annotations, no output schema), the description is incomplete. It lacks details on behavioral aspects (e.g., how 'n' is interpreted, what happens with invalid inputs), output specifics, and differentiation from siblings. While concise, it does not provide enough context for an AI agent to use the tool confidently without additional assumptions.

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 'n' with type 'integer' and 0% schema description coverage. The description adds minimal semantics by implying 'n' is an index (0-indexed) for perfect squares, which provides some context beyond the bare schema. However, it does not explain constraints (e.g., non-negative integers) or provide examples, leaving gaps in understanding. With low schema coverage, the description compensates slightly but not fully.

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: 'Get the nth perfect square (0-indexed).' It specifies the verb ('Get'), resource ('nth perfect square'), and indexing method ('0-indexed'), which is specific and unambiguous. However, it does not explicitly distinguish this tool from sibling tools like 'perfect_squares' or 'square_numbers', which might list or generate perfect squares differently.

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 ('arithmetic') and category ('basic_sequences'), but this is too generic to help differentiate among the many sibling tools (e.g., 'perfect_squares', 'square_numbers', 'nth_power_of_two'). There are no explicit instructions on when or when not to use it, or what alternatives exist.

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