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

Since no annotations are provided, the description carries the full burden of behavioral disclosure. It explicitly outlines the operational cost ('0.01 USDC per call via x402') and describes a crucial multi-step dependency involving the `paymentProof` parameter. These are highly valuable behavioral traits for an autonomous agent.

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 definition is highly concise, packing function, output format, financial constraints, and usage guidelines into a single, dense statement. It front-loads the most important operational details (cost and primary function).

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?

The description provides a robust definition for an AI extraction tool, covering not just the 'what' (extraction) but also the 'how' (JSON output) and the operational 'how' (payment flow). It addresses the most common gaps left by the absence of a structured output schema.

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?

While the input schema coverage is 100%, the description adds vital semantic context. It clarifies that the `fields` parameter acts as an exclusion filter (empty = full entity extraction) and explains the conditional nature of the `paymentProof` requirement on the first call.

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 that the tool 'Pulls' requested fields or named entities out of free text, defining it as an extraction tool that returns valid JSON. It specifically lists the types of entities extracted (names, dates, amounts, etc.), which helps differentiate it from simple summarization or classification 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?

It provides clear guidance on how the `fields` parameter should be used: if fields are provided, only those specific entities are extracted, while leaving it empty triggers the extraction of general named entities. This dual functionality serves as a practical guideline for tool invocation.

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