Validate JSON-LD

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

Annotations already cover safety (readOnly, openWorld, idempotent, non-destructive). The description adds behavioral detail beyond annotations: it performs specific validation checks and returns normalized, compact JSON ready to inject. This is meaningful extra context about the tool's behavior and output format, though it does not describe error handling or response details on failure.

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 two sentences with no fluff. It front-loads the core purpose and immediately lists concrete validation criteria, then states the return format. Every sentence earns its place, and the structure is highly scannable for an agent.

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 validation tool, the description covers what is validated, the input format (via schema), and the output (normalized JSON). It omits details like error messages or behavior on invalid input, but these are not critical for correct invocation. The tool is simple enough that the description is nearly complete.

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% for the single parameter 'jsonld', which already explains it accepts an object, array, or JSON string. The tool description does not add further parameter-specific semantics beyond what the schema provides. Per the baseline rule for high coverage, a 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 clearly states the tool validates JSON-LD objects and enumerates specific checks (required/recommended properties, FAQ/Breadcrumb structure, ISO dates, @context presence). It distinguishes itself from siblings like structured_data_audit by noting it uses the same rules but is for validation before publishing, and from schema_generate by focusing on validation rather than generation.

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 explicitly says 'before publishing', providing a clear usage context. It references 'same rules as structured_data_audit', which hints at an alternative tool but does not explicitly say when to use this instead. It also mentions returning normalized JSON ready to inject, implying the output is intended for publishing workflows. This is clear context but lacks explicit exclusions or alternative conditions.

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