stock_institute_hold_detail

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 covered. The description adds the data provenance (Sina Finance URL) and the return type (pandas.DataFrame), which is useful but not deep behavioral context (no rate limits, coverage years beyond the quarter start note, or data-freshness caveats).

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 is front-loaded, and the quarter explanation earns its space, but the raw URL and sphinx-style boilerplate (:type/:rtype) add clutter without improving agent decision-making. It is acceptable but not tightly edited.

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 simple two-parameter, read-only fetch with no output schema, the description supplies source, both parameter formats, and the return type. The only real omission is the shape/columns of the returned DataFrame, which is a minor gap given the annotations already convey safety.

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%, so the description carries the full load for both parameters. It explains that 'stock' is a stock code and, more importantly, decodes the opaque 'quarter' string with the report-type mapping (一季报=1, 中报=2, 三季报=3, 年报=4) and worked examples like "20191" and "20193", which the schema does not convey at all.

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 the source (新浪财经), the resource (机构持股详情), and the returned data (a stock's institutional holding data for a given reporting period). However, it never distinguishes this tool from near-identical siblings such as stock_institute_hold or stock_gdfx_holding_detail_em, so it stops short of a 5.

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?

There is no statement of when to use this tool versus the large family of related holding/股东 tools (stock_institute_hold, stock_gdfx_holding_detail_em, stock_report_fund_hold_detail, etc.). The agent must infer usage purely from the tool name.

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