extract_product_info

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It does convey that the tool reads product pages and returns extracted fields, which is useful. However, it does not mention output format, possible failures, limitations (e.g., non-e-commerce pages), or network behavior, leaving notable 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?

A single sentence efficiently states the tool's purpose and data coverage. It is front-loaded with the core action and then enumerates product aspects. Slight improvement could be a structured list, but no unnecessary words are present.

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?

The tool has only two parameters with full schema coverage and no output schema, so the description needs to clarify the return content. The list of extracted fields provides a solid picture of what the agent will receive, but it stops short of describing return format or edge cases. Still, it is reasonably complete for the tool's apparent simplicity.

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 100%, so the parameters are already well documented. The description adds no parameter-specific semantics beyond what the schema provides; it only lists output fields, not input parameter details. This matches the baseline for high schema coverage.

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 identifies the action (extract), the resource (product information from e-commerce URLs), and the scope (comprehensive data including images, stock, variants, price, dimensions, specs). No sibling tools exist, so no distinguishing is needed.

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 intended use case is clear: call this tool with e-commerce product page URLs to obtain product data. There are no explicit exclusions or alternatives, but the scope is well defined by the 'e-commerce URLs' phrase, which provides sufficient usage context.

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