divide

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

There are no annotations, so the description carries the behavioral burden. It covers the core behavior by stating that it returns the result and explicitly documents the b=0 error case, which is valuable edge-case transparency.

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?

Two short sentences with no filler. The formula is front-loaded, and the error condition is stated compactly in the second sentence. Every word earns its place.

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?

For a simple arithmetic tool, this is complete. It specifies inputs, the operation, the result, and the failure condition. No output schema exists, but the return value is trivially inferable as the numeric quotient.

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 schema already documents both parameters, so the baseline is 3. The description adds useful semantic context beyond the schema: the operation is order-sensitive (a / b), and b must not be zero.

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 states a specific verb ('Divide'), a clear resource ('the first number by the second'), and the exact formula (a / b). This unambiguously distinguishes it from sibling tools like add, subtract, and multiply.

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 tool's operation is clear enough that an agent can infer when to use it: whenever a quotient is needed. It does not explicitly name alternatives or exclusion cases, but the sibling tool set and the formula make the selection obvious.

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