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

No annotations are provided, so the description must fully disclose behavior. It indicates a read-only validation action and detection of missing schema types, but does not describe the return format, error handling, or limitations. For a tool without annotations, this leaves the agent uncertain about the tool's output, which is a significant 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?

The description is concise and front-loaded, stating the core function in the first segment. The bilingual text adds a minor redundancy for English-only use, but the '[FREE]' tag provides useful context without waste. Overall, it is efficient, though the French translation could be considered extraneous.

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, no annotations, and no output schema, the description covers the essential purpose but lacks details about what the tool returns. It is minimally viable for an agent to understand the tool's function, but the absence of output behavior leaves a gap. Given the simplicity of the tool, a brief note on response format would make it 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?

The input schema fully describes the only parameter 'url' with 100% coverage. The description adds no additional semantics beyond the schema, which is acceptable because the schema already provides all necessary details. With full schema coverage, 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 clearly states the tool validates JSON-LD structured data and detects missing schema types, using a specific verb and resource. It distinguishes from sibling tools which focus on SEO metrics and analysis, as none cover structured data validation. However, it does not explicitly name an alternative, so it lacks the full sibling differentiation of a 5.

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 implies the tool is for validating JSON-LD, but gives no explicit guidance on when to use it versus alternatives. It does not mention prerequisites, intended use cases, or tools not to use. The context is clear but not prescriptive, matching the 'implied usage' level.

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