multiply

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

With no annotations provided, the description carries full behavioral disclosure. It explicitly states the return format (dictionary with result or error message), the exact logging format ('MUL | {data.a} * {data.b} = {result}'), and that exceptions are caught and converted into an error response. This is thorough for a pure computation tool.

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 well-structured with Args, Returns, Logs, and Exceptions sections, and the core purpose is front-loaded. It is slightly more verbose than a simple multiply tool strictly requires, but each section contributes meaningful behavioral information rather than padding.

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 two-number multiplication operation, the description covers inputs, output contract, error behavior, and logging. Even though an output schema is marked as present, the description independently explains what the return value will be. Nothing essential for correct invocation is missing.

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 top-level data parameter has no schema description (0% coverage), but the description compensates by explaining that data is a TwoNumberOperation object containing a and b to be multiplied. This adds semantic clarity beyond the bare schema. It does not provide examples or edge-case notes, so it stops short of a 5.

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 opens with a specific verb and resource: 'Perform multiplication of two numbers provided in the data object.' It clearly distinguishes itself from the sibling arithmetic tools by naming the operation and the two inputs. No ambiguity about what the tool does.

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?

Usage is implied by the operation name and description: call this when you need the product of two numbers. However, it does not explicitly discuss when to use this tool versus alternatives like add, subtract, or power, nor provide any exclusion or preference guidance beyond the basic semantic.

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