industry_daily_collect

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

With no annotations provided, the description carries the full burden and does well: it discloses the source, the data type, the local SQLite destination, the batch scale, the freshness check, incremental backfill behavior, and the force flag semantics. This goes well beyond the structured schema.

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?

Two dense sentences carry all the key information: action, resource, storage, scale, incremental logic, and force behavior. There is no filler or repetition of the tool name.

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?

The description is largely complete for a collect-style tool, covering side effects, triggering conditions, and the force override. The main gap is the lack of explicit semantics for start_date, though the output schema reduces the need to describe return values.

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?

The force parameter is well described in both the schema and the description. The start_date parameter has no schema description and the description only indirectly hints at its meaning through '约90行业×5年数据' and the 20200101 default. Some inference is possible, but explicit meaning is missing.

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 description states a specific action ('批量采集'), a clear resource ('同花顺行业日行情 OHLCV'), an output destination ('写入本地 SQLite'), and scope ('约90行业×5年数据'). This clearly differentiates it from query-oriented siblings like industry_daily_query and from other collection tools.

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 explains the incremental behavior and the force option, giving clear context on when the tool will skip or refresh. However, it does not explicitly say when to use this tool versus siblings like industry_collect or industry_daily_query, nor does it state when not to use it.

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