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

Goes well beyond the readOnlyHint/openWorldHint annotations: it discloses that results are a limited free tier with paid upgrade links, that payment runs through x402 via Apify without an account, and gives concrete quota mechanics (1 per IP per UTC day, shared caller/ASN pool of 20, 20 globally per day). For a metered AI tool, these are exactly the operational facts an agent cannot get from structured fields.

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?

Purpose and the 'one text' constraint are front-loaded, followed by return/payment behavior and quotas. All sentences carry information, though the quota clauses are dense and packed into a single run-on final sentence that could be structured more scannably.

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 no output schema, the description still sketches the return shape ('limited free result and paid upgrade links'), and it covers cost/auth/quota behavior for a two-parameter open-world tool. The only gap is the exact structure of the free result, which an agent might want before parsing a response.

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 50% — 'text' is documented but 'question' has only a maxLength and no description. The description compensates by establishing that 'question' is a single yes/no question (not an open-ended prompt) and that 'text' is one fragment, adding real semantic constraints the schema lacks.

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+resource: 'Answers one yes/no question about supplied text using AI.' That is clearly distinct from sibling text tools like ai_extract, embed_text, summarize_article, and translate_text, which operate differently on text. The scope word 'one' further separates it from batch extraction 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?

Explicitly states both the intended case ('Use for one text') and exclusions ('Not for batch work or unrestricted monitoring'), which is more than most definitions provide. It stops short of naming the specific alternative sibling an agent should call for batch work, leaving that inference to the caller.

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