Validate structured data

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively communicates that the tool evaluates eligibility, not just schema validity, and gives concrete examples of failures. It does not mention output format or edge cases like missing JSON-LD, but the core behavioral trait is clearly disclosed.

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?

Two sentences with no wasted words. The main action is front-loaded, and the clarifying distinction with concrete examples earns its place by preventing a common misconception about the tool's behavior.

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?

For a single-parameter read-only validation tool, the description covers the essential question: what is checked, and what the interpretation should be. It does not describe the return format, but the absence of an output schema lowers the burden, and the tool's purpose is clear enough for an agent to select and invoke it correctly.

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%, and the single 'url' parameter is already documented in the input schema. The tool description adds no additional meaning about the parameter beyond what the schema provides, so a baseline score of 3 is appropriate.

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 states a specific verb ('Check') and a specific resource (a page's JSON-LD against Google's rich-result requirements). It also clarifies the tool's core distinction between valid JSON and rich-result eligibility, which separates it from generic schema validity checkers. Even without naming a sibling, the purpose is unmistakable.

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 gives clear context on when this tool matters: whenever the concern is whether schema earns a Google rich result, not merely whether it is valid JSON. It does not explicitly name an alternative or state when not to use it, but the examples imply the decision point well enough.

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