stock_changes_em

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

The annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds the data source (East Money) and return type (pandas.DataFrame) but does not disclose additional behaviors such as latency, data freshness, or any caveats. It does not contradict 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 a well-structured docstring with a title, URL, parameter specification, and return type. It is compact and front-loaded with the tool's identity, though the line breaks and repeated info (title and URL) slightly reduce precision.

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 indicates the return is a pandas.DataFrame but does not detail columns or contents beyond '盘口异动'. However, the tool has a single well-documented parameter and strong annotations, making it reasonably complete for a simple retrieval query. The lack of column details is a minor gap.

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 a 'symbol' string with a default, but the description provides an exhaustive list of 22 valid choices and explicitly states the parameter's meaning and type. This fully compensates for the schema's lack of enum or description, giving the agent complete information to pass a valid parameter.

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 retrieves 盘口异动 (market changes) data from East Money's 行情中心, with a URL and a specific list of supported symbols. The name stock_changes_em and title make the resource clear, though it doesn't explicitly differentiate from sibling stock data tools beyond the domain.

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 by listing valid symbol choices (e.g., '大笔买入', '封涨停板'), but provides no explicit guidance on when to use this tool versus alternatives, nor any exclusion criteria. The purpose is clear enough that an agent would infer when to use it, but there is no direct comparison with sibling tools.

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