macro_china_stock_market_cap

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which the description does not contradict. The description adds the return type (pandas.DataFrame) and source URL, which is useful. However, it does not disclose what columns or data range are included, so behavioral insight is limited.

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 short and to the point, including a source URL and return type in a structured docstring format. No extra fluff, but the inclusion of a URL and docstring markers is slightly verbose for a zero-param tool.

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?

The tool is simple (no params, no output schema), but the description does not explain what fields or statistics are included in the DataFrame. The tool name mentions 'stock_market_cap' while the description says 'trading statistics', creating potential ambiguity about the actual data content.

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 tool has zero parameters, so the schema already fully covers inputs. The baseline is 4, and the description does not need to add parameter details. It correctly mentions the return type.

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 '全国股票交易统计表' (national stock trading statistics) from East Money, and states the return type as pandas.DataFrame. While it omits an explicit verb like 'get' or 'list', the intent to fetch this table is clear and distinguishable from sibling macro tools.

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 provides no guidance on when to use this tool versus alternatives. It gives a source URL but no context, prerequisites, or exclusions. An agent must infer its applicability from the title alone.

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