lark-base

Operate Feishu Base tables, fields, records, views, and workflows via lark-cli.

1|Updated Apr 7, 2026
One-click install
npx skills add https://github.com/eatbreads/.agents --skill lark-base-eatbreads
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: lark-base
Source: https://github.com/eatbreads/.agents/tree/main/skills/lark-base
Command: npx skills add https://github.com/eatbreads/.agents --skill lark-base-eatbreads

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Provides authoritative, agent-friendly guidance and command-level workflows for operating Feishu multi-dimensional tables (Base) via lark-cli, reducing errors from guessing table/field names, misuse of APIs, and unsafe write operations.

Core Features & Use Cases

  • Safe command patterns: Enforces atomic lark-cli base +... usage, prevents using record-list for aggregation, and mandates pre-reading of reference docs for formula/lookup/workflow changes.
  • Schema & data management: Guides table/field creation, formula and lookup design, record upserts, attachments upload flow, and view/filter/sort/group/timebar configuration.
  • Analysis & dashboards: Directs when to use +data-query for server-side aggregation, how to build dashboard blocks (data_config), and pagination/limit best practices.
  • Workflows & permissions: Covers workflow creation/update/enable/disable rules and advperm/role lifecycle with safety checks for high-risk write/delete operations.
  • Operational guardrails: Token handling (wiki → obj_token), concurrency and batch limits, and explicit confirmation rules for destructive actions.

Quick Start

Inspect the target Base structure, read the relevant reference pages (formula/lookup/workflow), and then request the agent to produce the exact lark-cli base +... commands needed to safely complete your schema or record task.

Frequently Asked Questions about lark-base

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create and manage Feishu Base tables and records using lark-cli?

To manage Feishu Base tables and records, use atomic lark-cli base commands for schema creation, record CRUD, and upserts. You must retrieve exact table and field names using table-list and field-list before writing to ensure safe operations.

What is the best way to perform server-side aggregation in Feishu Base?

The best way to perform server-side aggregation in Feishu Base is using the data-query command. Avoid using record-list for aggregation; instead, use data-query for cross-table aggregation and apply pagination and batch limits to optimize performance.

How do I configure formulas and lookups in Feishu bitable?

To configure formulas and lookups in Feishu bitable, you must read command-specific reference docs and guides before execution. Use atomic lark-cli base commands for formula and lookup creation, ensuring you retrieve exact field names beforehand to prevent unsafe writes.

Can I automate workflows and manage permissions in Feishu Base?

Yes, you can automate workflows and manage permissions in Feishu Base. Use lark-cli to create, update, enable, or disable workflows, and manage advperm and role lifecycles with explicit safety checks for high-risk write and delete operations.

How do I build dashboards in Feishu Base?

To build dashboards in Feishu Base, configure dashboard blocks using data_config settings. Use lark-cli base commands to define the data configuration, and apply pagination and limit best practices when querying the underlying data sources.

What are the limitations when writing data to Feishu Base?

Limitations when writing data to Feishu Base include concurrency and batch limits, token handling constraints like wiki to obj_token conversion, and formula or workflow constraints. Explicit confirmation is required for destructive actions to prevent unsafe writes.