product

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states what the tool does (calculates product) but doesn't mention error handling (e.g., empty arrays, non-numeric elements), performance characteristics, or return format. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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, efficient sentence that directly states the tool's purpose with zero wasted words. It's appropriately sized for a simple mathematical operation and front-loads the core functionality.

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 mathematical tool with no annotations, 0% schema description coverage, and no output schema, the description is incomplete. It doesn't explain what happens with empty arrays, non-numeric inputs, overflow scenarios, or the return format. Given the context signals, more behavioral and parameter details would be needed for adequate completeness.

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%, so the description must compensate. It mentions '数组' (array) which aligns with the 'numbers' parameter, but provides no details about element types (numbers vs. other types), array size limits, or handling of special values. The description adds minimal semantic value beyond the parameter name.

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 '计算数组所有元素的乘积' (calculates the product of all elements in an array) clearly states the verb ('计算' - calculate) and resource ('数组所有元素的乘积' - product of all array elements). It distinguishes from siblings like 'sum' (which adds) or 'multiply' (which might handle pairwise multiplication), but doesn't explicitly contrast with them.

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 doesn't mention when this tool is appropriate compared to 'multiply' (which appears to handle two numbers) or other mathematical operations in the sibling list. No context about input types or constraints is provided.

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