extract_schema

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

No annotations exist, so the description must carry the burden. It discloses that the tool extracts structured data and reports errors, implying a read-only operation. However, it does not explicitly state non-destructiveness, authentication needs, or rate limits.

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?

Single sentence, front-loaded with the core action and outputs. No redundant 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 one parameter, no output schema, and missing annotations, the description provides sufficient context: the tool extracts and lists specific structured data types and errors. Slightly less informative for a read-heavy tool, but adequate.

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 100% schema coverage, the description adds no new information about the 'url' parameter beyond the schema's 'Page URL' description. No format constraints or examples are 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 the verb 'extract' and the resource 'JSON-LD structured data from a page', and specifies what it returns (schema.org @types, microdata itemtypes, parse errors). It distinguishes from sibling tools like audit_page and check_robots by focusing on structured data extraction.

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 implicitly indicates usage for extracting structured data, but lacks explicit guidance on when to use this tool versus alternatives (e.g., audit_page). No exclusions or context are provided.

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