natural_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 that the tool generates numbers in a range, but does not specify whether the range is inclusive or exclusive, what happens with invalid inputs (e.g., negative numbers), or if there are any limits on range size. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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: 'Generate natural numbers (positive integers) in a given range.' It efficiently conveys the core functionality without unnecessary words. The parenthetical note about domain and category is brief and adds context without detracting from clarity. Every sentence earns its place, making it highly efficient.

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 (a simple generation tool), no annotations, no output schema, and low schema description coverage, the description is incomplete. It lacks details on behavior (e.g., inclusivity of range, error handling), parameter usage, and output format. For a tool with 2 parameters and no structured guidance, more context is needed to ensure the agent can use it correctly.

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', which implies the 'start' and 'end' parameters, but does not explain their semantics (e.g., that 'start' and 'end' define the bounds, default values, or that they are integers). This adds minimal meaning beyond the schema, 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: 'Generate natural numbers (positive integers) in a given range.' It specifies the verb ('generate'), resource ('natural numbers'), and scope ('in a given range'), making it easy to understand. However, it does not explicitly differentiate from sibling tools like 'integers_in_range' or 'whole_numbers', which could offer similar functionality, so it falls short of 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 no guidance on when to use this tool versus alternatives. It mentions the domain ('arithmetic') and category ('number_systems'), but this is too vague to help an agent choose between this and sibling tools like 'integers_in_range' or 'range_value'. There are no explicit instructions on when to prefer this tool or what scenarios it is best suited for.

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