math_divide

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 only states that division is performed and omits important behavior such as what happens when b is 0, whether the result is a float, and any error handling or precision details.

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 a single short sentence with no filler, and the operation is front-loaded. However, it is under-specified rather than efficiently complete, so it earns a middle score rather than a higher one.

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?

With two required numeric parameters and no output schema, the description omits essential context: operand order and division-by-zero behavior. The tool is simple, but an agent selecting and invoking it correctly would need more information.

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?

Schema description coverage is 0% and the description does not map a to a dividend or b to a divisor. Since division is non-commutative, failing to specify operand order is a material omission that the description does nothing to resolve.

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 uses a specific verb ('divide') and a clear object ('two numbers'), and the operation is semantically distinct from siblings like math_add and math_multiply. It does not specify which operand is the dividend and which is the divisor, but the core purpose is unambiguous.

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?

There is no guidance about when to use math_divide versus math_multiply, math_add, or any alternative. No examples, prerequisites, or disambiguating conditions are provided; the only implied usage comes from the tool name itself.

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