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

With no annotations, the description carries the full burden and does well: it discloses the first-page-only limit (max 5 rows, no pagination), the per-call cost of 0.011 USDC, that empty results are not safety findings, and explicitly that nonempty row semantics are unverified. It stops short of 5 only because return shape is left unspecified.

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 purpose is front-loaded in the first line, but the remainder is a dense, somewhat repetitive wall of caveats ('No completeness or safety guarantee' restates the earlier certification disclaimer). It is defensible but could be tightened without losing behavioral content.

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?

Given no annotations, no output schema, and an opaque free-form parameter, the description does substantial work covering cost, pagination limits, and safety caveats. It remains incomplete on what a returned row actually contains, which matters for an unverified-semantics tool.

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 0% and the single 'arguments' object is free-form with additionalProperties true, so the schema carries no meaning. The description compensates partially by naming company_id and pointing to get_cn_data_tool_schema("v3_promotion_keyword") for the actual argument contract, but the caller must still make a second lookup call.

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 opening line states a clear verb+resource: 'query enterprise online promotion keywords', which is specific enough to distinguish it from most siblings. It doesn't explicitly differentiate from the closely related cn_data_v3_promotion_overview sibling, so it stops short of a 5.

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 operational context ('Use company_id from cn_data_v3_company_detail', 'One selected Chinese company data tool call', 'Additional pages require separate requests') but never states when to choose this over the promotion_overview sibling or other company data tools. Usage is implied by the survey framing 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.