is_divisible

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's function but does not cover critical behavioral aspects: it doesn't mention error handling (e.g., division by zero), performance characteristics, or output format. For a tool with no annotations, this leaves significant gaps in understanding how the tool behaves in edge cases.

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: a single sentence that directly states the tool's purpose, followed by domain/category tags. Every word earns its place with no redundancy or fluff, making it easy to parse quickly.

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 low complexity (2 simple integer parameters) and lack of annotations or output schema, the description is minimally adequate. It explains what the tool does but misses key contextual details: no output schema means the return value (likely a boolean) is unspecified, and behavioral aspects like error handling are omitted. It's complete enough for basic understanding but lacks depth for reliable use.

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 description adds meaningful context beyond the input schema. The schema only defines 'a' and 'b' as integers with 0% description coverage. The description clarifies that 'a' is 'the first number' and 'b' is 'the second number', and specifies their relationship ('divisible by' with 'remainder is zero'). This compensates well for the low schema coverage, though it doesn't detail constraints like non-zero 'b'.

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: 'Check if the first number is divisible by the second number (remainder is zero).' It specifies the verb ('check'), resource ('first number' and 'second number'), and the exact condition ('remainder is zero'). However, it does not explicitly differentiate from siblings like 'modulo' or 'remainder', which are related but distinct operations, 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 no guidance on when to use this tool versus alternatives. It mentions the domain ('arithmetic') and category ('number_theory'), but this is too generic given the many sibling tools (e.g., 'modulo', 'remainder', 'is_even', 'is_odd') that handle similar concepts. There are no explicit when/when-not instructions or named alternatives, leaving usage ambiguous.

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