whole_numbers

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 generates numbers in a range but does not clarify key behaviors: whether the range is inclusive or exclusive, if it returns a list or sequence, error handling for invalid inputs, or performance characteristics. This leaves significant gaps in understanding how the tool operates beyond its basic purpose.

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, followed by domain and category information. There is no unnecessary verbiage, and the structure is efficient, though the domain/category details could be considered slightly extraneous if not needed for tool selection.

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 (2 parameters, no annotations, no output schema), the description is insufficient. It lacks details on parameter usage, behavioral traits (e.g., output format, error handling), and differentiation from siblings. Without an output schema, the description should ideally hint at return values, but it does not, leaving the agent with incomplete context for effective tool invocation.

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 2 parameters with 0% description coverage, so the description must compensate. It mentions 'a given range' but does not explain the 'start' and 'end' parameters—such as their default values (0 and 10), whether they are inclusive, or if they accept negative values. This lack of detail fails to adequately supplement the schema, resulting in incomplete parameter semantics.

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: 'Generate whole numbers (non-negative integers) in a given range.' It specifies the verb ('generate'), resource ('whole numbers'), and scope ('in a given range'), making the function unambiguous. However, it does not explicitly differentiate from sibling tools like 'integers_in_range' or 'natural_numbers', which might have overlapping functionality, preventing a perfect 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 minimal guidance by mentioning the domain ('arithmetic') and category ('number_systems'), but it does not specify when to use this tool versus alternatives. For example, it does not explain how it differs from sibling tools such as 'integers_in_range' or 'natural_numbers', leaving the agent without clear usage context or exclusions.

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