audit_schema

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

With no annotations provided, the description fully carries the behavioral burden. It clearly states read-only behavior, network usage rules ('Zero network when given schema_json'), determinism, and rule-based processing. No contradictions.

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 (approx. 100 words), front-loaded with the main purpose, then modes, usage guidelines, and parameter rules. Every sentence adds essential information; no fluff.

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 tool with 3 parameters and no output schema, the description covers inputs, behavior, and use cases thoroughly. It lacks details about the exact format or contents of the validation report output, but that is not critical given the tool's simplicity and the clarity of its purpose.

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 coverage is 100%, so baseline is 3. The description adds value by explaining mutual exclusivity rules ('Either url or schema_json must be provided, not both') and precedence, and clarifies the purpose of respect_robots. This goes beyond the schema's own descriptions.

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 and resource: 'Validate JSON-LD structured data against Schema.org rules and AI-citation best practices.' It clearly distinguishes from sibling tools like audit_page by specifying focus on JSON-LD audits.

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?

Explicitly states when to use: 'focused JSON-LD audits, or to validate a schema block you're about to ship.' Provides an alternative: 'For a full page audit... use audit_page instead.' Also covers parameter precedence ('if both are provided, schema_json wins').

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