stock_analyst_detail_em

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds the return type (pandas.DataFrame) and the data source, but says nothing about rate limits, page/row limits, or what happens with an invalid analyst_id — modest added value beyond 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 opening line repeats a long site-navigation path and a raw URL already implied by the title annotation, and the epytext tags (:param/, :type/, :return/, :rtype:) add some noise. The substantive content (indicator choices, analyst_id source) is buried after the boilerplate.

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 usefully states the return type and the meaning of each indicator, and it flags the dependency on stock_analyst_rank_em for the ID. For a two-parameter read-only lookup this is close to complete, missing only guidance on result shape per indicator.

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 description coverage is 0% and the indicator property has no enum in the schema, so the description carries the burden: it enumerates the three valid indicator values ({"最新跟踪成分股", "历史跟踪成分股", "历史指数"}) and explains where analyst_id must be obtained. That is genuine value beyond the schema, though it does not explain the semantic difference between the three indicator views.

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 identifies a specific resource (analyst detail from Eastmoney's analyst index) and enumerates the three data views available via the indicator parameter. It implicitly distinguishes itself from stock_analyst_rank_em by naming that tool as the source of analyst_id, though the bulk of the opening line is boilerplate site-path text rather than purpose.

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?

It states that analyst_id comes from ak.stock_analyst_rank_em(), which is a useful prerequisite and routes the agent to the right sibling first. However, it never says when to choose one indicator over another or when this tool is preferred over related research-report tools, so usage is only implied.

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