lucas_u_v

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 sequences but does not describe output format, error handling, computational limits, or side effects. For a mathematical computation tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

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. There is no unnecessary information, and it efficiently communicates the core functionality. However, the inclusion of domain and category in parentheses, while brief, could be considered slightly extraneous but does not significantly detract.

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 sequence calculation with 3 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on parameter meanings, output format, and behavioral traits. The tool's purpose is clear, but without additional context, an agent would struggle to use it effectively.

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 3 parameters (n, P, Q) with 0% description coverage, meaning no parameter details are provided in the schema. The description only mentions 'parameters P, Q' without explaining what n, P, or Q represent, their valid ranges, or their roles in the calculation. This fails to compensate for the schema's lack of documentation.

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 Lucas U_n and V_n sequences with parameters P, Q.' It specifies the verb ('calculate'), the mathematical objects ('Lucas U_n and V_n sequences'), and the required parameters ('P, Q'). However, it does not explicitly differentiate from sibling tools like 'lucas_number' or 'lucas_sequence', which might be related, so it misses the highest score.

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 ('recursive_sequences'), but this is too vague to inform usage decisions. There is no mention of prerequisites, typical use cases, or how it differs from similar tools in the sibling list.

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