Retrieve Feishu attendance punch-in/out task records via the attendance API.
npx skills add https://github.com/mykcs/myk-skills --skill lark-attendance-mykcs
Please help me install this Agent Skill. Skill: lark-attendance Source: https://github.com/mykcs/myk-skills/tree/main/lark-attendance Command: npx skills add https://github.com/mykcs/myk-skills --skill lark-attendance-mykcs
It solves the problem of manually checking your Feishu (Lark) attendance punch-in/out history by giving you a direct way to query your own attendance task records.
schema command before calling the action, preventing field guessing.employee_type="employee_no" and keeps user_ids as an empty array to align with the required query contract.Ask the assistant to run the lark-attendance query to fetch your attendance punch records.
High-intent search queries and answers about installing and using this skill.
You can query your Feishu attendance punch records by instructing the assistant to run the attendance query, which calls the Feishu attendance API to retrieve your personal punch-in and punch-out task history.
No, you cannot look up attendance history for other employees. The query enforces a read-only scope with an empty user_ids array, restricting retrieval to your own personal attendance task records.
Yes, you need lark-cli installed to retrieve your attendance punch-in history. The Skill executes the attendance.user_tasks.query command through the lark-cli dependency to fetch your records.
The Feishu attendance API query requires the parameter employee_type set to employee_no and user_ids as an empty array. It also enforces schema-first parameter validation to prevent field guessing before calling the action.
Schema-first validation is required for your Feishu attendance query to inspect the API payload structure with the schema command beforehand, preventing field guessing and ensuring the request parameters match the query contract.
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