stock_comment_detail_scrd_desire_em

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds that it returns a pandas DataFrame from a specific East Money URL, which implies a web data fetch, but it does not disclose potential rate limits, authentication needs, or data update frequency. No contradiction with 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 description is concise and well-structured, using a docstring format with source URL, parameter, and return sections. It is front-loaded with the title and contains no unnecessary fluff, though the return line repeats the title wording.

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 one-parameter read-only tool, the description gives the source, parameter, and return type, which is adequate. However, without an output schema, it does not describe the DataFrame's columns or the nature of '市场参与意愿' beyond the label, leaving an agent uncertain about the exact data structure.

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 string 'symbol' with a default and no description. The description compensates by explaining that symbol is a stock code (股票代码) and provides an example URL with '600000'. However, it does not specify the expected format (e.g., six-digit with leading zeros) or acceptable exchanges, leaving some ambiguity.

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 tool as fetching East Money's 'market heat - market participation willingness' data for a given stock symbol, with a source URL and return type. It distinguishes itself from sibling stock_comment_detail tools by specifying the data category (desire/participation willingness), though it does not explicitly name alternatives.

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 provided on when to use this tool versus the many sibling stock_comment_detail tools (e.g., stock_comment_detail_scrd_focus_em). It does not state prerequisites, symbol format requirements, or whether it should be preferred over other market-heat tools.

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