get_json_ld

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

With no annotations, the description carries the burden of behavioral disclosure. It clearly states the return behavior (JSON-LD data) and gives a fallback hint, implying that absence of data should lead to get_page_content. It doesn't mention edge cases like multiple JSON-LD blocks or malformed data, but for a zero-parameter read-only tool, it is sufficiently 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 and well-structured: first sentence states the core function, second adds context and usage guidance. No wasted words, and it front-loads the key information.

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 tool's low complexity, empty input schema, and existing output schema, the description provides complete context. It states what the tool does, gives examples, explains the fallback relationship, and refers to the current page context. No significant gaps remain.

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 tool has zero parameters, so the baseline is 4. The description adds no parameter-specific details, but none are needed since schema coverage is 100% (empty properties).

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 tool returns schema.org structured data (JSON-LD) embedded in the current page, citing specific examples (Recipe/Product/Article). It differentiates from siblings by explicitly directing users to 'Check here before falling back to get_page_content'.

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?

Provides explicit when-to-use guidance by instructing to check this tool before falling back to get_page_content. It also motivates usage by noting that many sites embed clean structured data, making it the preferred first choice for extracting structured content.

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