stock_zh_a_minute

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

Annotations already establish read-only, idempotent, and non-destructive behavior. The description adds that the tool returns a pandas.DataFrame and explains adjustment modes (qfq/hfq), but it does not disclose limitations like data availability windows, rate limits, or column details. Thus it provides moderate added context but not rich behavioral transparency.

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 structured as a docstring with a URL and parameter list, which is efficient and scannable. However, the line 'return: specific data' is vague and adds little value, and the title/annotations duplicate some content. It is concise but not optimally polished.

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?

Without an output schema, the description's return information ('specific data', pandas.DataFrame) is insufficient to tell an agent what columns or time ranges to expect. It also omits any limitations, data source caveats, or guidance on selecting this tool among many similar stock data functions. The parameter details are strong, but overall context is only minimally complete.

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 has 0% description coverage, making the description the sole source of parameter semantics. It comprehensively explains each parameter: symbol with example 'sh000300', period with valid values 1/5/15/30/60, and adjust with three modes (empty/qfq/hfq). This fully compensates for the lack of schema descriptions.

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 resource as '股票及股票指数历史行情数据-分钟数据' (stock and index historical market minute data), making the tool's purpose evident. However, it lacks an explicit verb and does not differentiate from sibling tools like stock_zh_a_hist or stock_zh_a_hist_min_em, so it misses the full 5-point criterion.

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 for minute-level historical data through its title and parameter explanation, but it does not explicitly state when to use this tool over alternatives or provide any exclusion guidance. Sibling tools with similar names exist, yet no comparative direction is given.

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