schema_validate

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

Despite no annotations, the description discloses key behaviors: detecting all <script> blocks, checking required fields, suggesting missing schemas based on URL patterns, and listing possible verdicts. It also states that no authentication is needed. It does not cover rate limits or error details beyond fetch_error, but is generally transparent.

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 concise, using seven well-structured sentences that front-load the main purpose. Every sentence adds value without redundancy, making it efficient for an AI agent to parse.

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 simple input (one parameter) and the presence of an output schema (so return values need not be fully described), the description adequately covers input, behavior, and output summary. It includes verdicts and recommendations, making it complete for the tool's complexity.

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?

With only one parameter (url) and 0% schema description coverage, the description compensates by explaining that the URL is to be fetched and that it works on any public URL. This adds meaning beyond the schema alone, though more detail on URL format or constraints could improve it.

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 that the tool fetches a URL and validates its JSON-LD structured data schemas, using specific verbs and resources. It distinguishes from sibling tools like 'inspect_url' by focusing on schema validation rather than general page analysis.

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 clear context for usage, noting that authentication is not required and it works on any public URL. However, it does not explicitly state when to use this tool versus alternatives like 'inspect_url' or 'page_analysis', though the specialization is implied.

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