stock_zh_valuation_comparison_em

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, which covers the safety profile. The description adds minimal behavioral context, only mentioning that the return is a pandas.DataFrame. It does not disclose any data freshness, pagination, or potential quirks beyond what annotations provide.

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 short and front-loaded with the title, but includes a long URL that adds little value for an AI agent. It is not bloated, and the docstring-style parameter/return lines are structured clearly, though they could be more informative.

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 only one parameter and no output schema, the description should clarify the symbol format, supported markets (e.g., A-shares vs HK), and what the returned DataFrame contains. It only says '估值比较' without explaining the output columns or any limitations. The 'zh' in the tool name suggests A-shares, but the description does not confirm this.

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 has one parameter 'symbol' with no description, and schema description coverage is 0%. The description only says 'param symbol: 股票代码' (stock code), which is tautological with the parameter name. The default value 'SZ000895' hints at an exchange prefix format, but this is not explicitly explained, leaving ambiguity about the expected symbol format.

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 gives the full path '东方财富-行情中心-同行比较-估值比较' (Eastmoney - Market Center - Peer Comparison - Valuation Comparison), which clearly identifies the data source and resource. It distinguishes from sibling tools like stock_zh_scale_comparison_em by specifying '估值比较' (valuation comparison), but lacks an explicit verb such as 'get' or 'fetch'.

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 implies the tool is used for obtaining valuation comparison data for a stock, but it does not explicitly state when to use it versus alternatives like stock_hk_valuation_comparison_em or stock_zh_valuation_baidu. No exclusions or alternative guidance is provided.

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