validate_structured_data

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

The description adds behavioral detail beyond the readOnlyHint and openWorldHint annotations: it fetches a web page, extracts three structured-data formats, validates against Schema.org types, and reports missing properties. It does not cover all edge cases, but the annotations already cover the read-only nature, so this is adequate.

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 with no filler. The action and core behavior are front-loaded, and the SEO-audit use case is a useful closing context.

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 a single required parameter, no output schema, and read-only/open-world annotations, the description covers the tool's purpose, input, and high-level output behavior ('reports missing properties'). It could specify the exact return shape, but it is sufficiently complete for basic invocation.

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 single 'url' parameter is already fully documented in the input schema. The description does not add parameter-specific meaning, but it does not need to; baseline 3 is appropriate.

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 states a specific verb and resource ('Fetch a web page and extract all structured data') and adds concrete detail about validation against Schema.org types and missing-property reporting. This clearly distinguishes it from siblings like extract_meta_tags or validate_url.

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?

'Useful for SEO audits' gives a clear context for when to use the tool. It does not explicitly name alternatives or exclusion cases, but the use case is sufficient for an agent to select it among the listed siblings.

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