create_analysis_workflow

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

注释已表明只读、非破坏性和幂等性，描述在此基础上补充了并行执行和综合获取数据的行为特征，增加了透明度。

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?

描述仅用两句话就涵盖了功能、效率优势和适用场景，信息密度高且首句直接点明核心，结构紧凑。

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?

在无输出模式的情况下，描述虽未明确返回格式，但说明了工具能获取所有投资决策所需资料，对于复杂的组合工作流而言已较为全面，但仍可考虑补充错误处理或结果结构信息。

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?

输入模式已经对每个参数有完整描述（代码、市场、步骤），描述中重复了步骤的枚举值但未添加超出模式的语义信息，因此未显著提升参数理解。

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?

明确说明了工具的功能是执行完整的个股研究工作流，并在描述中列出获取的数据类型（报价、技术指标等），同时通过与逐一调用其他工具的对比强调其高效性，有助于区分于其他工具。

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?

描述给出了具体的使用场景示例（‘帮我把 2330 完整分析’），并提示比逐一调用更高效，但未明确说明何时不应使用或与其他组合工具（如 get_full_stock_analysis）的区别。

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