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

With no annotations provided, the description must disclose behavioral traits. It mentions it is paid and provides a cost estimate, and emphasizes that output is guaranteed to match the schema. However, it lacks details on error handling, performance, or limitations such as token limits or failure modes.

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 long, front-loading the core purpose and key differentiator (schema-constrained decoding). Every sentence adds value, and there is no wasted text.

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 has three parameters (two required), nested objects, and no output schema, the description is moderately complete. It explains the core functionality and cost but omits details about the 'instruction' parameter, example usage, or return value structure.

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 0%, meaning no parameter descriptions exist in the schema. The description adds no detail about the parameters beyond their existence implied in the purpose. The 'instruction' parameter is not mentioned at all, leaving its meaning unclear.

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 extracts structured data as JSON matching a provided schema, using a specific verb ('Extract') and resource ('structured data from text'). It distinguishes itself from siblings like 'classify' or 'summarize' by emphasizing schema-constrained decoding.

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 usage for structured extraction when a JSON schema is provided, but does not explicitly state when to use or avoid this tool, nor does it mention alternatives among the listed siblings. The cost hint provides some context, but guidance is minimal.

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