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

With no annotations, the description carries the full burden and does disclose real behavioral traits: per-call pricing (0.011 USDC), that additional pages require separate requests, that null means unknown, that a summary/header is not the underlying record list, and explicit data-quality/ownership/compliance disclaimers. It omits auth/permission requirements, but the pricing, pagination and null semantics are substantive beyond a bare restatement.

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, but the body is a run-on mix of Chinese and English with overlapping disclaimers ('No completeness or safety guarantee' repeats the earlier completeness/safety certification clause). Several sentences earn their place (pricing, pagination, null semantics), but the framing is somewhat disorganized.

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 and an opaque single-argument schema, completeness rests on the description, which does hint at return shape ('A summary/header is not the underlying record list') and gives cost/pagination caveats. It still leaves the concrete return structure and argument fields to the separate get_cn_data_tool_schema call, so it is adequate rather than self-sufficient.

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 schema is an opaque 'arguments' object with additionalProperties, so the description must compensate. It names the key field (company_id), its source (cn_data_v3_company_detail), and points to get_cn_data_tool_schema('v3_promotion_overview') for the full argument shape, which is helpful but leaves the actual argument structure to an external lookup.

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 Chinese opening () states a specific verb (query) and resource (enterprise online promotion overview), which an agent can distinguish from keyword-level siblings like cn_data_v3_promotion_keyword. However, it stops short of naming any sibling or clarifying the boundary of 'overview' vs. detail tools, leaving differentiation to inference.

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?

The description supplies a concrete prerequisite: 'Use company_id from cn_data_v3_company_detail,' routing the agent to how the key argument is obtained, and notes it is 'One selected Chinese company data tool call.' It gives no explicit when-not guidance or comparison against the sibling promotion/data tools, so usage is implied rather than directive.

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