tetranacci_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 states the calculation but does not describe key behavioral traits such as input constraints (e.g., valid range for 'n'), performance characteristics (e.g., recursion depth limits), error handling, or output format. For a computational tool with no annotations, this leaves significant gaps in understanding how the tool 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, with the core purpose stated first. The additional domain and category information is brief and relevant. There is no wasted verbiage, making it efficient for an agent to parse, though it could be slightly more structured (e.g., separating 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 computational nature, no annotations, no output schema, and low schema coverage, the description is incomplete. It lacks details on input validation, output format, error conditions, and performance limits. While it states the purpose, it does not provide enough context for reliable agent invocation without 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 0% description coverage, with one parameter 'n' of type integer. The description adds minimal semantic context by implying 'n' is the index in the Tetranacci sequence, but it does not specify meaning (e.g., zero-based vs. one-based), constraints, or examples. Since schema coverage is low, the description partially compensates but not sufficiently for a higher score.

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 the nth Tetranacci number (4th order Fibonacci).' It specifies the verb ('Calculate'), resource ('Tetranacci number'), and mathematical context. However, it does not explicitly differentiate from sibling tools like 'fibonacci' or 'tribonacci_number', which would be needed for a score of 5.

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 and category ('Domain: arithmetic, Category: recursive_sequences'), but this is generic and does not help an agent choose between similar tools like 'fibonacci', 'tribonacci_number', or other sequence calculators. No explicit when-to-use or when-not-to-use instructions are given.

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