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

Goes well beyond the annotations: discloses the price (0.04 USDC), chain (eip155:8453), x402 v2 payment transport, the required client library, and crucially that an unpaid call returns a 'payment required' result and charges nothing. It also flags that labels come from an external classifier and that non-English coverage is not guaranteed — exactly the operational caveats annotations cannot express.

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 usage lead, then return shape, then payment mechanics, then caveats — a sensible front-loaded order with no wasted filler. It is dense and the payment-precondition text is long, but every clause is operationally necessary for a paid tool.

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, but the description names the returned keys ('keywords, not_classified'), and the payment/auth model is fully specified so an agent knows it cannot succeed without an x402 client. The open-world and non-English caveats close the remaining gaps for a single-parameter lookup.

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, and the description adds the keyword-count ceiling plus a genuine semantic caveat that non-English keywords may not classify reliably — meaning for the sole input parameter beyond its type. It does not discuss the lowercasing/dedup behavior, which the schema already covers.

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 ('Search intent ... for up to 10 keywords'), enumerates the label taxonomy it returns, and names the upstream classifier (DataForSEO Labs Search Intent). No sibling tool in the list performs intent classification, so the agent can distinguish it from keyword_metrics, keyword_difficulty, and keyword_ideas purely from this sentence.

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?

'Use it to decide whether a keyword suits an informational, commercial or transactional page' gives a concrete decision context, and the 10-keyword cap implies batching limits. It stops short of exclusions or pointing to a sibling (e.g. keyword_metrics for volume), so it is clear context without alternatives.

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