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

With no annotations at all, the description still carries the key behavioral facts an agent needs before calling: a per-call cost (0.003 USDC via x402), a batch limit of 50, and an English-only input constraint. It stops short of describing failure behavior or the exact response shape, which keeps it out of the top band.

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?

A single dense sentence pair that front-loads what the tool does, then appends the two operational constraints an agent must know. No filler and nothing buried.

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?

There is no output schema, so the description does the minimum needed by naming the return values (positive/negative label plus probability), and the payment mechanics are covered by the schema. Only the absence of non-English or error-case behavior keeps it below complete.

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 description coverage is 100%, so both `text` and `paymentProof` are already fully documented, including the 402 retry flow. The description's mention of batching to 50 merely restates the schema, so baseline 3 is appropriate.

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 ('Classifies English text as positive or negative') plus the output form (probability score) and a batch ceiling. It is clearly distinguishable from generic siblings like ai_classify and ai_extract, though it never names the closest alternative explicitly.

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?

Usage is only implied: the English-only restriction and the 50-text batch cap hint at appropriate inputs, but there is no statement of when to prefer this over ai_classify or how to handle non-English content. The payment retry flow lives entirely in the schema, not the description.

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