dingtalk_aisearch_person

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It only states the search dimensions and does not mention whether the operation is read-only, requires special permissions, has rate limits, or what the response format is. While 'search' implies a read operation, the description lacks explicit context about side effects or limitations.

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 concise parenthetical phrase, listing dimensions without fluff. It is front-loaded with the core purpose ('企业人员多维搜索') and immediately enumerates the relevant attributes. However, it is a fragment rather than a complete sentence, which slightly reduces accessibility.

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 parameter, no output schema) and the informative query schema, the description is mostly adequate for a basic search tool. However, it lacks usage guidance and any indication of expected output structure, and with no annotations, the agent has to infer safety and side effects. The description is not as minimal as a pure tautology but leaves clear gaps in operational context.

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 input schema covers 100% of the single parameter 'query' with a clear description and an example (自然语言描述，如：技术部负责前端的同事). The tool description adds the list of searchable fields, which provides context for what kinds of queries are valid, but the schema already does the heavy lifting. Baseline 3 is appropriate.

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 identifies a search tool for enterprise personnel across multiple dimensions (name, department, position, responsibility, superior/subordinate, phone, employee ID). The verb is implicit in '搜索' (search), and the resource is '企业人员' (enterprise personnel). However, it does not explicitly differentiate itself from sibling tools like dingtalk_contact_user_search or dingtalk_contact_user_search_mobile, though '多维' (multi-dimensional) hints at a broader semantic search.

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 the many contact-related siblings (e.g., dingtalk_contact_user_search, dingtalk_contact_user_search_mobile, dingtalk_contact_dept_search). There is no mention of alternatives, prerequisites, or specific scenarios where an AI-powered multi-dimensional search would be preferred over more targeted tools.

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