get_hk_stock_analysis

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the tool provides '数据驱动的分析报告' (data-driven analysis reports) and mentions return content, but lacks critical behavioral details: whether it requires authentication, has rate limits, how recent the data is, or if it performs calculations versus fetching pre-computed reports. The disclaimer about not being investment advice is helpful context but insufficient for a mutation-free analysis tool.

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 well-structured and appropriately concise. It opens with the core purpose, includes a disclaimer, then clearly documents parameters and returns in labeled sections. Every sentence adds value, with no redundant information. The only minor improvement would be integrating the disclaimer more seamlessly rather than as a separate clause.

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?

Given the tool's moderate complexity (2 parameters, analysis types), no annotations, but with an output schema that presumably documents the return structure, the description is minimally adequate. It covers parameters well and outlines return content, but lacks behavioral context (data freshness, sources, limitations) that would be important for an analysis tool. The output schema reduces the need to detail return values, but overall completeness is just sufficient.

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 description adds significant semantic value beyond the input schema, which has 0% description coverage. It explains that 'code' is a Hong Kong stock code with format example 'hk.00700', and that 'analysis_type' has three specific options ('fundamental', 'technical', 'comprehensive') with a default of 'fundamental'. This compensates well for the schema's lack of descriptions, though it doesn't detail what each analysis type entails.

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 the tool's purpose: '提供基于数据的港股分析报告' (provides data-driven Hong Kong stock analysis reports). It specifies the resource (Hong Kong stocks) and distinguishes it from general stock analysis tools like 'get_stock_analysis' by focusing on Hong Kong markets. However, it doesn't explicitly differentiate from other Hong Kong-specific tools like 'get_hk_stock_basic_info' or 'get_hk_stock_realtime_data' in terms of analysis depth.

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 provides no guidance on when to use this tool versus alternatives. With many sibling tools for Hong Kong stock data (e.g., 'get_hk_balance_data', 'get_hk_profit_data', 'get_hk_stock_basic_info'), there's no indication of whether this tool aggregates data from those sources or serves a different purpose. The disclaimer '而非投资建议' (not investment advice) is useful but doesn't address tool selection.

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