Check structured data (JSON-LD)

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

Beyond the readOnlyHint and openWorldHint annotations, the description adds valuable behavioral detail: tolerates arrays and @graph, flags malformed JSON-LD, checks specific schema properties, and provides a ready-to-paste Organization example when none exists. No contradiction with annotations.

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 at three sentences, front-loaded with the primary action, and every additional detail (tolerated structures, specific checks, fallback behavior) earns its place. No redundant or filler content.

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 description covers the tool's core behavior, including what it validates and how it handles malformed or missing JSON-LD. Given the simple parameter schema and lack of output schema, it is sufficiently complete, though a brief note on return format would make it fully comprehensive.

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?

The input schema has full coverage (100%) for the single 'url' parameter, and the description does not add additional parameter-level semantics. The baseline of 3 applies because the schema already documents the parameter adequately.

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 uses a specific verb ('Extract and validate') and resource ('schema.org JSON-LD on a page'), and enumerates specific entity types checked (Organization, SoftwareApplication, FAQPage, BreadcrumbList). This clearly distinguishes it from sibling SEO tools like check_https or run_lighthouse.

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 when to use the tool: when a page's structured data needs to be validated or extracted. It does not explicitly mention alternatives or exclusions, but the detailed scope of checks makes the use case evident in the context of sibling tools.

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