JSON-LD構造化データ生成

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

With no annotations provided, the description carries the burden of behavioral disclosure. It states that empty items are automatically omitted from output and that the return value is a JSON object and a <script> snippet. This adds value beyond the input schema, though it could mention safety (read-only) or authentication requirements.

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 composed of four concise sentences, each providing essential information: purpose, supported types, output behavior, and return value structure. No filler or redundancy; it is efficiently front-loaded with critical details.

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 no output schema and no annotations, the description partially compensates by describing the output format and empty omission behavior. However, it lacks usage examples, error handling notes, or explanation of how the 'type' parameter determines which input properties are required. For a tool with nested objects (5 parameters, 1 required), the description could be more complete.

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 baseline is 3. The description adds overall context (empty omission, output format) but does not per-parameter details beyond what the schema already provides. No additional semantic clarification for individual parameters is given.

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 it generates schema.org compliant JSON-LD structured data, listing the supported types (organization, faqpage, service, breadcrumb). The verb '生成する' (generate) and resource are specific, and it distinguishes itself from unrelated sibling tools (e.g., contrast_check, webp_convert).

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 lists the four supported schema types, implying when to use this tool (e.g., for generating company info or FAQ structured data). It does not explicitly state when not to use it or provide alternative tools, but sibling tools are dissimilar, so exclusion is not critical. The guidance is clear but could be more explicit.

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