dingtalk_contact_user_get
Batch fetch DingTalk user profiles (name, department, email) using a list of user IDs.
Instructions
根据 userId 批量获取用户详细信息(姓名、部门、邮箱等)
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| user_ids | Yes | 逗号分隔的 userId 列表 |
Batch fetch DingTalk user profiles (name, department, email) using a list of user IDs.
根据 userId 批量获取用户详细信息(姓名、部门、邮箱等)
| Name | Required | Description | Default |
|---|---|---|---|
| user_ids | Yes | 逗号分隔的 userId 列表 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It mentions 'batch' retrieval and example fields but does not describe behavior for invalid userIds, whether partial success is possible, permission requirements, or error handling. This is a significant gap for a read tool with no annotation coverage.
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, focused sentence that front-loads the core action. It is concise and to the point, with no filler. While it could additionally mention usage context, it earns a high score for efficiency.
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), the description is somewhat complete: it states the purpose and provides example return fields. However, it lacks details on return format, error handling, and any constraints (e.g., max number of user_ids), leaving notable gaps for an agent relying solely on the description.
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 already documents the single parameter (user_ids) as a comma-separated list, providing 100% coverage. The description adds no new parameter syntax details but clarifies the batch nature and example output fields. Baseline 3 is appropriate since the schema does the heavy lifting.
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 function: it batch-retrieves detailed user information (name, department, email, etc.) based on userId. The verb '获取' (get) is specific, the resource is '用户详细信息' (user detailed info), and the method '根据 userId' distinguishes it from search or self-info tools.
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 does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions. Usage is implied by the name and description (when you have userIds and need their details), but there is no comparison with sibling tools like get_self or search.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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