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

Annotations already declare the safe-read profile (readOnly, idempotent, non-destructive, open-world), and the description goes well beyond them: exact pricing ($0.10 per call over x402 on Base), the x-credit-token prepaid header, the absence of a free tier, no API key requirement, and a 6K char per-document limit. An agent knows the cost, auth path and size constraints before calling.

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?

Front-loaded with the core value proposition and ordered sensibly (what it does, how to call, why batch, limits, price, auth). It is dense and slightly salesy in the per-call cost comparison, but nearly every sentence carries actionable 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 already present, the description need not explain return values and instead states the shape qualitatively ('one schema-enforced JSON object per document, in order'). Combined with pricing, auth, per-document limits and required input, nothing material is missing for correct invocation.

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 the baseline is 3, but the description adds real invocation detail: how to pass multiple documents ('text1=…&text2=… or texts= with ||| separators') and the required text1. Minor friction: the 'texts=' form it advertises does not appear as a property in the input schema, which could send an agent down a wrong path.

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?

States a specific verb and resource with explicit scope: batch extraction of the same field list across up to 10 texts. It directly positions itself against the sibling by calling itself 'the pipeline version of ai-extract', so an agent can separate the batch and single-document tools without opening either schema.

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?

Gives concrete usage contexts ('agents parsing feeds, inboxes, scrape batches and receipt piles') that imply when batching pays off, and referencing ai-extract signals the single-document alternative. It never states an explicit when-not-to-use condition (e.g. use ai_extract for a single document), so the routing is inferable rather than spelled out.

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