multiply

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the basic function ('Multiply two numbers together') and return value, but doesn't cover important aspects like error handling (e.g., overflow, invalid inputs), performance characteristics, or side effects. This leaves significant gaps for an AI agent to understand the tool's behavior fully.

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 highly concise and well-structured, with a clear purpose statement followed by labeled sections for 'Args' and 'Returns'. Every sentence earns its place by providing essential information without redundancy, 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 (simple arithmetic), the presence of an output schema (which handles return values), and the description's coverage of parameters and purpose, it is mostly complete. However, the lack of usage guidelines and limited behavioral transparency (e.g., no error handling details) prevents a perfect score, as these could aid an AI agent in more nuanced scenarios.

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 semantics beyond the input schema, which has 0% description coverage. It explicitly defines 'a' as 'First number' and 'b' as 'Second number', clarifying their roles. However, it doesn't specify constraints like number types (e.g., integers vs. decimals) or ranges, which could be useful for more complex use cases.

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 with a specific verb ('Multiply') and resource ('two numbers'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'add' or 'divide', which would require mentioning it performs multiplication specifically rather than other arithmetic operations.

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 like 'add' or 'divide'. It lacks context about scenarios where multiplication is appropriate, such as calculating areas or scaling values, and doesn't mention any prerequisites or exclusions.

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