stock_hk_hist_min_em

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is clear. The description adds useful context such as the data source URL and the return type (pandas.DataFrame), but does not disclose behavior like date inclusiveness, timezone handling, or potential limitations of the data source. It adds some value but lacks deeper behavioral details.

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 and well-structured as a docstring, with each parameter on its own line and a clear source URL. Every line provides useful information without unnecessary fluff. The structure is easy for an agent to parse, though it lacks a brief narrative overview.

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?

For a tool with five parameters and no output schema, the description covers the parameters and return type, but omits important details such as the exact columns of the returned DataFrame, the date/time format expected for start_date and end_date, and how the period interacts with daily minute data. The unusual default values (e.g., '1979-09-01 09:32:00') are not explained, leaving ambiguity 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?

The input schema only lists parameters with defaults and no descriptions, so the description carries the full burden. It provides per-parameter documentation: symbol (股票代码), period (choice of '1','5','15','30','60'), adjust (choice of '','qfq','hfq'), start_date (开始日期), and end_date (结束日期). The valid choices for period and adjust are explicitly listed, which is essential. However, date formats are not specified, and the odd default values are unexplained.

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 daily minute-level (分时) quotes for Hong Kong stocks from Eastmoney, with the title '东方财富网-行情-港股-每日分时行情'. The resource and data type are specific, and the tool name 'stock_hk_hist_min_em' aligns with the description, distinguishing it from daily or spot HK stock tools. However, the verb is not explicitly stated (e.g., 'fetch' or 'get'), which slightly reduces clarity.

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 implies usage: provide a HK stock symbol, a minute period, adjustment, and date range to retrieve minute-level history. However, it does not explicitly state when to use this tool versus alternatives like stock_hk_hist (likely daily) or stock_hk_spot (real-time). No exclusions or when-not-to-use guidance is provided.

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