lark-attendance
open.feishu.cn
Query your Lark/Feishu attendance check-in records via CLI
What is lark-attendance?
lark-attendance is a skill for coding agents that enables querying personal attendance and check-in records from Feishu (Lark) using the lark-cli tool. It wraps the Feishu Attendance API with automatic parameter injection so agents never need to prompt users for standard fields like employee_type or user_ids.
- Queries user attendance check-in records from Feishu via lark-cli
- Automatically injects required parameters (employee_type, user_ids) without prompting the user
- Provides schema inspection for API parameters before making calls
- Enforces correct scope (attendance:task:readonly) for API access
- Reads shared authentication config from lark-shared SKILL.md at runtime
How to install lark-attendance
npx skills add null --skill lark-attendance- lark-cli must be installed and available in PATH
- lark-shared SKILL.md must be present (provides authentication and permission handling)
- Feishu app must have the attendance:task:readonly scope granted
How to use lark-attendance
- 1.Install the skill: npx skills add null --skill lark-attendance
- 2.Ensure lark-cli is installed and lark-shared SKILL.md is accessible
- 3.Run lark-cli attendance --help to confirm the CLI is working
- 4.Before calling any API, inspect the parameter schema: lark-cli schema attendance.user_tasks.query
- 5.Call the query method: lark-cli attendance user_tasks query with appropriate --params or --data flags
- 6.employee_type is always set to employee_no automatically — do not override
- 7.user_ids array is always set to [] automatically — do not override
- 8.Review returned check-in records for the requested date range
Use cases
- Check your own attendance punch-in/punch-out history for a date range
- Audit attendance records programmatically inside a coding agent workflow
- Retrieve check-in data as part of an automated HR or reporting task
- Developers using Claude Code or Cursor who need to query Feishu attendance data
- Teams automating HR workflows via Feishu APIs
- Engineers building internal tools on top of the Feishu attendance system
lark-attendance FAQ
No. Both are injected automatically: user_ids is always [] and employee_type is always employee_no. You must not ask the user for these values.
The attendance:task:readonly scope must be granted to your Feishu app.
Authentication is handled by lark-shared SKILL.md, which must be read before using this skill.
Run lark-cli schema attendance.user_tasks.query before calling the API to inspect the expected --data and --params structure.
Currently only user_tasks.query is available, which retrieves attendance check-in records.
Full instructions (SKILL.md)
Source of truth, from open.feishu.cn.
name: lark-attendance version: 1.0.0 description: "飞书考勤打卡：查询自己的考勤打卡记录" metadata: requires: bins: ["lark-cli"] cliHelp: "lark-cli attendance --help"
attendance (v1)
CRITICAL — 开始前 MUST 先用 Read 工具读取 ../lark-shared/SKILL.md，其中包含认证、权限处理
默认参数自动填充规则
调用任何 API 时，以下参数 必须自动填充，禁止向用户询问：
| 参数 | 固定值 | 说明 |
|---|---|---|
employee_type | "employee_no" | employee_type始终等于"employee_no" |
user_ids | []（空数组） | user_ids始终等于[] |
填充示例
当构建 --params 参数时，自动注入上述字段：
employee_type保持"employee_no"不变
当构建 --data 参数时，自动注入上述字段：
{
"user_ids": [],
...用户提供的参数
}
注意：
user_ids数组保持为空[]，employee_type保持"employee_no"不变。
API Resources
lark-cli schema attendance.<resource>.<method> # 调用 API 前必须先查看参数结构
lark-cli attendance <resource> <method> [flags] # 调用 API
重要：使用原生 API 时，必须先运行
schema查看--data/--params参数结构，不要猜测字段格式。
user_tasks
query— 查询用户考勤打卡记录
权限表
| 方法 | 所需 scope |
|---|---|
user_tasks.query | attendance:task:readonly |
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