extract_structured_data

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

Without annotations, the description must carry the full burden. It explains what the tool does (extract structured data as JSON) but does not disclose important behaviors like failure modes, dynamic content handling (though the javascript_enabled parameter hints at it), rate limits, or authentication needs. Some transparency but incomplete.

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 two sentences, front-loaded with the core action and results. Every sentence serves a purpose: first defines the tool, second adds context for when to use it. No redundant or verbose language.

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 three parameters, nested objects, and no output schema, the description is minimal. It does not describe the structure of the returned JSON, how multiple data_types interact, or any error handling. While adequate for a simple tool, it lacks completeness for an agent to fully anticipate behavior.

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 67%, so baseline is 3. The tool description does not add any additional meaning beyond the schema's parameter descriptions (e.g., explaining how options affect extraction or the nuances of data_types). It simply reiterates the overall purpose without enhancing parameter understanding.

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 verb 'Extract structured data' and the resource 'any webpage', with explicit output format 'as JSON'. It lists specific data types like tables, lists, key-value pairs, and gives use cases (pricing lists, feature comparisons), distinguishing it from sibling tools that handle articles, links, or screenshots.

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 context on when to use the tool (e.g., processing data tables, pricing lists, feature comparisons) but does not explicitly contrast with sibling tools like extract_article or extract_links. It lacks explicit when-not-to-use guidelines, but the use-case examples are sufficient to guide selection.

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