智能搜索接口

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

No annotations provided, so the description must carry the burden. It discloses key behaviors: automatic keyword extraction, path mapping, mixed Chinese-English support, and relevance sorting. It does not discuss edge cases or output details, but for a simple search tool, this is sufficient transparency.

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 with clear sections (core capabilities, use cases, priority directive). It uses bullets and examples efficiently without fluff. Every sentence contributes to understanding the tool.

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 single-parameter tool with no output schema, this description is quite complete. It explains purpose, usage scenarios, behavioral mechanics, and next steps. It doesn't detail return format, but states relevance sorting, which adequately covers what the agent needs to know for invocation.

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?

Schema already defines 'query' as natural language, but the description adds meaningful examples and clarifies expected input types (e.g., '查找用户登录接口', '获取订单列表'). This goes beyond the schema's minimal description, giving the agent concrete grounding for what to provide.

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 it's an intelligent search tool that maps natural language queries to API paths, with explicit examples of query types. It distinguishes itself by calling itself the 'AI's preferred search tool' and positioning semantic search, differentiating from sibling tools like search_api.

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 explicit use cases (functional needs, module inquiries, business scenarios) and gives a direct directive: '优先使用此工具进行语义搜索，再用 get_api_detail 获取详情' (prefer this for semantic search, then use get_api_detail for details). This clearly tells the agent when to use it and what to use next.

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