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

Beyond the readOnly/idempotent/openWorld annotations, the description discloses the extraction method (heuristic, explicitly not OCR), the pricing model ($0.01/call over x402 on Base), the auth options (prepaid x-credit-token header for unlimited calls, or 1 free call/day), and that no API key is required — rich operational context an agent needs before invoking.

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 extraction scope is front-loaded in the first clause, and the OCR/pricing caveats follow logically. It is slightly dense with payment boilerplate, but every sentence carries usable information.

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 an output schema present, return-value documentation is unnecessary, and the description fully covers what the tool extracts, the required preprocessing, the cost/auth model, and the input requirement. Nothing an agent needs to call it correctly is missing.

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?

There is a single parameter with 100% schema description coverage; the description only restates 'Required input: text', adding no format, size, or encoding guidance beyond what the schema already provides. Baseline 3 applies.

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-plus-resource ('Pull totals, IBAN, dates out of receipt text') and enumerates the exact fields extracted (totals, amounts, VAT hints, IBANs, dates, emails, invoice numbers), so an agent can distinguish it from generic extraction siblings like ai_extract or web_extract.

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 gives an explicit usage precondition and exclusion: 'Not OCR — convert a scan to text first, then send it here.' That tells the agent when this tool is the wrong choice. It stops short of naming a sibling alternative for plain-text extraction, so it is not a full 5.

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