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

With no annotations, the description carries the full behavioral burden. It doesn't say whether the output is returned as a string, written to a file, or injected into a page, nor whether it validates the generated markup or has side effects. For a generator tool with zero structured disclosure, this is a real gap.

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?

One well-formed sentence, front-loaded with the verb and resource, and every word earns its place. It is terse, which is fine for the conciseness dimension even though other dimensions suffer from the thinness.

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?

No annotations, no output schema, 0% parameter description coverage, and an undocumented nested item shape leave the agent guessing about the return value, error behavior, and input constraints. The description would need to do far more work here.

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 single parameter is an array whose item properties are cryptically named 'q' and 'a' with 0% schema description coverage. The description's 'question/answer pairs' does clarify those abbreviations, adding genuine meaning, but it says nothing about array size, ordering, or content constraints.

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?

States a specific verb (generate), a specific resource (FAQPage JSON-LD structured data), and the input form (question/answer pairs). The named resource clearly separates it from siblings like generate_product_schema or generate_open_graph, though it never explicitly says so.

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 phrase 'from question/answer pairs' implies the trigger condition (you have FAQ content and need structured data), but there is no statement of when to prefer this over validate_json_ld or the other generate_* siblings, and no prerequisites or exclusions.

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