stock_zh_ah_daily

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

Annotations already indicate readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is clear. The description adds the data source (Tencent Finance) and return type (pandas.DataFrame), which is useful but does not disclose any behavioral quirks like date range inclusivity, symbol format requirements, or handling of missing data. No contradiction with 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 follows a structured docstring format with a clear title, a source URL, and parameter descriptions. It is concise, with no redundant phrases, and each line adds meaning. The URL is arguably extra but serves as a reference.

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 no output schema, the description compensates by specifying the DataFrame return type and the data source. However, it leaves gaps: the symbol format is ambiguous (the URL shows 'hk01033' but the default symbol is '02318'), and the adjust parameter's empty default is not explained. The description is adequate for a simple tool but not fully 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?

Schema coverage is 0%, but the description provides explicit ':param' entries for all four parameters: symbol, start_year, end_year, and adjust, including type hints and examples. The adjust parameter maps 'qfq' to forward adjustment and 'hfq' to backward adjustment, which adds meaning beyond the bare string schema. However, it does not clarify the expected format of symbol (e.g., with or without 'hk' prefix) nor the behavior when adjust is empty.

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 explicitly states '腾讯财经-港股-AH-股票历史行情' (Tencent Finance HK AH stock historical quotes) and the return line specifies '指定股票在指定年份的日频率历史行情数据' (daily frequency historical market data for a given stock in a given year). This is a specific verb+resource combination that distinguishes it from sibling tools like stock_zh_ah_spot, which provides real-time spot data.

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 retrieving daily historical data for AH stocks via the return line, but it does not explicitly state when to use this tool over alternatives such as stock_zh_ah_spot or stock_zh_ah_name, nor does it mention exclusions or prerequisites. The absence of cross-references to siblings leaves the selection criteria implicit.

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