stock_a_high_low_statistics

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

Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds the return type (pandas.DataFrame) and the source URL, which are useful but do not disclose deeper behaviors like data frequency, freshness, or exact columns. 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 is compact and follows a standard docstring format with title, URL, param, and return sections. Each line serves a purpose, and there is no superfluous text. It is appropriately sized, though the URL might be redundant for an agent.

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 provides a basic return description (a DataFrame of high/low counts) but lacks details on columns, time period, or data granularity. Given the tool's simplicity (one parameter), this is adequate but leaves room for interpretation about the exact output structure.

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 schema has no description or enum for the 'symbol' parameter (0% coverage), so the description compensates by listing allowed values: 'all', 'sz50', 'hs300', 'zz500'. However, it does not explain what each value represents (e.g., which index or market scope), so the agent knows valid inputs but not their semantic differences.

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 states the tool's purpose via its title '乐咕乐股-创新高、新低的股票数量' (number of stocks hitting new highs and lows) and the return type mentions '创新高、新低的股票数量'. It is specific about the resource, but lacks an explicit verb like 'get' or 'fetch', and does not distinguish from sibling tools such as stock_rank_cxg_ths which also deals with new highs.

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?

No guidance is provided on when to use this tool versus alternatives. The description only includes parameter choices and a source URL, but does not specify scenarios, exclusions, or mention any related tools. This is minimal and leaves the agent without selection criteria.

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