gangtise_research_outline

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

With no annotations provided, the description must fully disclose behavioral traits. It only mentions the tool returns Markdown content and that the input supports A-share codes (from schema). There is no information about potential limitations (e.g., rate limits, data freshness, AI generation quality, or failure conditions), leaving significant gaps for an agent.

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 a single, front-loaded sentence that conveys the core action, input, and output format without any superfluous words. Every token contributes value, making it highly efficient.

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 simplicity (one required parameter, no output schema), the description provides the essential information. However, compared to the rich set of sibling tools (e.g., gangtise_one_pager, gangtise_summary_list), it lacks context on how the outline relates to other research outputs (e.g., length, level of detail) and any potential restrictions beyond A-share support.

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 description for the single parameter 'securityCode' already specifies '仅支持 A 股证券代码' (only supports A-share stock codes). The tool description does not add further meaning beyond this, so it meets the baseline expectation for a well-covered schema without adding extra semantic depth.

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 retrieves an AI-generated research outline for a given security and returns Markdown content. It uses specific verbs ('获取'/'get') and a distinct resource ('AI生成公司研究提纲'/'AI-generated company research outline'), effectively differentiating it from sibling tools like gangtise_research_download (full reports) or gangtise_research_list (list of reports).

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 such as gangtise_research_download or gangtise_investment_logic. An agent receives no hints about typical use cases, prerequisites, or exclusion criteria, leaving the decision entirely to inference from the purpose.

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