stock_gdfx_holding_teamwork_em

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is fully covered by structured data. The description adds the return type (pandas.DataFrame of top-10 shareholders) and the source URL, which is modest additional context. It discloses nothing about auth, rate limits, or empty-result behavior, so it does not go beyond the annotation baseline meaningfully.

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 purpose line is front-loaded, which is good, but the raw docstring skeleton (URL, :param:, :type:, :return:, :rtype:) is machine-note phrasing rather than narrative and the bare URL adds little selection value. It is compact and not bloated, but not optimally structured for agent consumption.

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?

For a single-parameter data-fetch tool with rich annotations and no output schema, the description covers the parameter values and return type. What is missing is the semantic distinction from sibling shareholder tools and any clarifying meaning of '股东协同'/'十大股东', which matters given the dense sibling cluster. Adequate but incomplete.

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% – the schema only declares a string named 'symbol' with default '社保' and no enum. The description compensates by enumerating the valid values ({全部, 个人, 基金, QFII, 社保, 券商, 信托}), which the agent would otherwise not know. It still does not explain what 'symbol' conceptually filters (holder category), so it is strong but not complete.

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 names the data source hierarchy (EastMoney data center → shareholder analysis → shareholder teamwork → top 10 shareholders) and the return subject, so the resource is identifiable. However, there is no explicit verb and, critically, no differentiation from the very close sibling stock_gdfx_free_holding_teamwork_em (the free-float counterpart) or other stock_gdfx_holding_* tools. It reads largely as a restatement of the tool name/title, keeping it at minimum-viable clarity.

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 offers no when-to-use guidance, no prerequisites, and never names an alternative. An agent must guess whether this is the right shareholder tool among the many siblings. Nothing communicates the selection condition (e.g. 十大股东 vs 十大流通股东).

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