validate_schema

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

With no annotations provided, the description carries the full burden. It discloses the checks performed (required fields, @context, @type, common issues) but does not explicitly state that the tool is read-only or non-destructive, nor does it describe the output format or error handling.

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 extremely concise with two sentences, front-loaded with the action and followed by specific details. Every word contributes meaning without repetition or 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?

Given the tool's simplicity (single param, no output schema, no annotations), the description covers the core purpose and checks. However, it lacks details on the return value or result format, which could be important for an AI agent to interpret validation results.

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 schema covers 100% of the parameter and its description. The tool description adds value by listing what the validation checks, which gives context beyond the parameter type. This enhances understanding of how the parameter is used.

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 an existing JSON-LD schema, specifying the verb 'validate' and the resource. It lists specific checks (required fields, @context, @type, common issues), distinguishing it from sibling generator tools.

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 does not explicitly provide usage guidelines or contrast with alternatives. However, the sibling tools are all generators, so the validation purpose is implicitly clear, but lacking explicit when-to-use or when-not-to-use guidance.

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