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

No annotations are provided, so the description carries the full behavioral burden, and it delivers: it discloses free/no-Key access, that calls still count toward usage and rate limits, and the three progressive-loading response modes (catalog vs. summary vs. full text). That is substantive operating context an agent could not 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?

Front-loads the purpose and the bold when-to-use warning, then layers in loading semantics and cost. Efficient and well-structured, though the progressive-loading detail partially duplicates the schema parameter descriptions.

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 an output schema present, return values need no explanation, and the description nonetheless covers purpose, selection condition, load strategy, and cost/limits. For a zero-required-param lookup tool this is complete for correct invocation.

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 100%, so the schema already documents q/lang/slug, including the '留空' defaults. The description's progressive-loading notes largely restate what the param descriptions say, adding little beyond the schema. Baseline 3 is appropriate.

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 resource (产品文档/wiki) and enumerates exactly what it covers: field units, definitions/口径, common misuse, cross-market differences. This is inherently distinguishable from the surrounding data-fetch siblings like ashare_kline or ashare_quote. An agent knows this is the reference/knowledge tool, not a market-data tool.

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?

Gives an explicit when-to-use rule ('不确定某字段的含义、单位、口径时先用这个查'), an explicit recommendation over the alternative of answering from memory, and a concrete progressive-loading path (目录 → 摘要 → 全文). Nothing is left to inference.

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