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 cost model ('free, no charge/不扣费'), the returned volume (2 records), and an attribution obligation with exact citation strings. What it omits is failure behavior for an unknown dataset value and whether results are deterministic/fresh — minor against the strong cost and citation disclosure.

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 when-to-use block is front-loaded and well marked, but the entire content is duplicated in Chinese and English, roughly doubling length without adding information. The citation-style instruction at the end is relevant but tacked on and interrupts the tool description's flow.

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?

An output schema exists, so return values need no explanation, and the description covers purpose, trigger conditions, cost, and dataset options. Completeness is only slightly short of full: nothing explains what the limit parameter changes or how invalid dataset values behave.

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 0%, so the description must compensate, and it does for the critical parameter by enumerating the accepted dataset values (projects / issuances / licenses / market / regulatory) which the bare string schema does not. The 'limit' parameter is only implicitly referenced via '2 sample records' and is never explained, so it is not fully covered.

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: 'returns 2 real sample records from one dataset', and immediately frames it against the paid siblings ('before paying', '调用任何付费查询工具之前'). An agent can distinguish this free-preview tool from query_projects/query_market etc. without opening any schema.

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?

Explicit when-to-use: call before any paid query tool to verify fields, data density, and source links, and call when the user asks 'what does this data look like / which fields / is it worth buying'. It also names the alternative class (paid query tools) that this precedes, leaving nothing to inference.

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