stock_hot_follow_xq

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, covering the safety profile. The description adds the return type (pandas.DataFrame) and the source URL, but does not disclose potential behavioral traits such as data freshness, rate limits, or whether scraping may be required. Given the annotations, the additional context is moderate but not extensive.

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 compact, consisting of a title line, a URL, and concise param/return docstrings. It is front-loaded with the purpose and structured logically, though the URL line and redundant title could be considered minor clutter. Every sentence contributes useful information.

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 description covers the parameter choices, return type, and source, which is adequate for a simple one-parameter tool with no output schema. However, it lacks details on the DataFrame's columns, data update frequency, or potential quirks of the Xueqiu source. For a basic ranking tool, this is sufficient but not thorough.

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 schema provides only a parameter name and default value with 0% description coverage. The description compensates by explicitly listing the valid choices for 'symbol' ("本周新增" and "最热门"), adding meaningful semantics beyond the schema. It could further explain the impact of each choice, but the literal meanings are fairly self-explanatory.

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 a specific verb+resource: it provides a follow/popularity ranking for Shanghai/Shenzhen stocks from Xueqiu, with a URL to the relevant page. It distinguishes itself from siblings like stock_hot_tweet_xq and stock_hot_rank_em by focusing on the '关注排行榜' (follow ranking), though it doesn't elaborate on what exactly that entails.

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?

No guidance is given on when to use this tool versus alternatives. Among many sibling hot/rank tools, there is no explicit differentiation or context about scenarios where this specific follow ranking is preferable. The description only provides the source and parameters, leaving the agent to guess the intended use case.

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