Validate JSON-LD

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

Annotations already declare readOnly and non-destructive behavior; the description adds useful behavioral context: it performs specific checks, normalizes/compacts the JSON, and returns an injectable object. It does not describe what is returned when validation fails, which is a small but 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?

Two front-loaded sentences carry purpose, validation rules, and return value with no filler. Every phrase earns its place.

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?

With one parameter and no output schema, the description covers the input, the checks performed, and the success return value. It omits failure behavior (what happens if validation fails or what the error shape looks like), which is essential for a validation tool.

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 input schema already fully documents the jsonld parameter's accepted forms (string, object, array), so the description adds no new parameter-level semantics. The description's 'one or more' loosely matches the schema's array case but adds no detail beyond it.

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?

Names a specific verb (Validate) and resource (JSON-LD objects) and enumerates what is checked. It is clearly distinct from schema_generate and structured_data_audit, but it only references structured_data_audit via 'same rules' rather than explicitly distinguishing the two.

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?

'Before publishing' and 'ready to inject' provide a clear temporal use case, and the list of checks indicates when it is appropriate. It does not explicitly state when not to use it or name the alternative tool to use for auditing already-published pages.

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