stock_zh_a_hist_pre_min_em

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true. The description adds the return type (pandas.DataFrame), data source URL, and the pre-market inclusion, which are useful but do not disclose deeper behaviors such as date handling, rate limits, or data granularity specifics. It does not contradict the annotations.

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 description is concise, front-loaded with the source and data type, and uses a structured docstring format for parameters. The URL is potentially distracting but not excessive. No significant redundancy beyond the title repeating in both description and annotation.

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 omits critical context such as how the date is determined (no date parameter), what the output DataFrame columns are, and how pre-market data is defined. This is especially problematic because the tool name says 'hist' yet there is no date parameter, making it unclear whether this returns data for a single day or requires external date context.

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?

With schema_description_coverage at 0%, the description compensates minimally by providing parameter types and Chinese descriptions for symbol, start_time, and end_time. However, the descriptions are terse ('股票代码', '开始时间', '结束时间') and lack format examples or constraints beyond the defaults, leaving ambiguity about symbol format and time semantics.

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 clearly identifies the tool as providing pre-market and intraday minute data for Shanghai/Shenzhen/Beijing A-shares from East Money, which distinguishes it from regular A-share minute history tools like stock_zh_a_hist_min_em. The verb '获取' is implicit but the resource and data scope are explicit.

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?

There is no explicit guidance on when to use this tool versus alternatives. The description only states what it returns, without mentioning scenarios or exclusions. The 'pre-market' distinction is implied by the name and title but never turned into actionable advice for tool selection.

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