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feishu_get_user

Retrieve user details from Feishu/Lark, including name, avatar, email, phone, and department information. Get your own profile or specify a user ID to access specific user data.

Instructions

获取用户信息。不传 user_id 时获取当前用户自己的信息;传 user_id 时获取指定用户的信息。返回用户姓名、头像、邮箱、手机号、部门等信息。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_idNo用户 ID(格式如 ou_xxx)。若不传入,则获取当前用户自己的信息
user_id_typeNo
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the tool's dual behavior (current vs. specified user) and lists return fields (name, avatar, email, phone, department), which adds useful context. However, it doesn't mention authentication requirements, rate limits, error conditions, or whether this is a read-only operation (though implied by 'get'), leaving some behavioral gaps.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, followed by conditional usage and return details in two concise sentences. Every sentence adds value without redundancy, making it efficient and easy to parse for an AI agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no annotations and no output schema, the description provides basic purpose, usage, and return fields, which is adequate for a simple lookup tool. However, it lacks details on authentication, error handling, or data format specifics, which could be important for robust agent operation. It's minimally complete but has room for improvement.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 50% (only user_id has a description). The description compensates by explaining the semantics of user_id (when to omit it for current user info) and implies the purpose of user_id_type through context. It adds meaning beyond the schema, especially for user_id, though it could elaborate more on user_id_type's role.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with a specific verb ('获取' meaning 'get') and resource ('用户信息' meaning 'user information'). It distinguishes between two modes: getting current user info when no user_id is provided, and getting specified user info when user_id is provided. This is precise and actionable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context on when to use each mode (with or without user_id), which helps the agent understand the tool's behavior. However, it doesn't explicitly mention when to use this tool versus sibling tools like 'feishu_search_user', which could help differentiate between lookup and search operations. The guidance is good but lacks sibling comparison.

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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