What problem it solves

Using Lark/Feishu business capabilities often requires working across many services and API levels, while automation also needs concise interfaces and predictable output. The project addresses these needs with human- and agent-friendly shortcuts, curated API commands, raw endpoint access, and documented agent skills.

Key features

• Agent-ready skills — Structured skills cover setup, authentication, service operations, workflows, and custom skill creation for AI Agent integration.

  Source: README, skills

• Three-layer command access — Users can choose shortcuts for common operations, curated API commands for platform endpoints, or raw API calls for direct endpoint access.

  Source: README

• Broad business-domain coverage — The command surface includes calendar, messaging, documents, drive files, markdown, Base, Sheets, Slides, tasks, wiki, mail, meetings, and other Lark/Feishu workflows.

  Source: README

• Scriptable output and request controls — Commands provide structured formats, pagination controls, dry-run previews, and schema introspection for workflows that need precise inspection or scripting.

  Source: README

• Security-aware access — The tool documents agent-related risks and includes credential storage and request-protection controls for authorized operations.

  Source: README

Quick start

Copied verbatim from the project's README.

npx @larksuite/cli@latest install

# 1. Configure app credentials (one-time, interactive guided setup)
lark-cli config init

# 2. Log in (--recommend auto-selects commonly used scopes)
lark-cli auth login --recommend

# 3. Start using
lark-cli calendar +agenda

Who it may suit

Inference: may suit individual developers operating Lark/Feishu from a terminal, AI Agent builders needing documented skills, and enterprise teams embedding the CLI with centralized credentials and a restricted command surface.

Topics to discuss

• Which additional Lark/Feishu workflows should receive dedicated agent skills?

• How can the three-layer command system be extended while preserving a stable interface?

• Which enterprise embedding patterns and audit controls should the extension packages support next?

Written by ReadmeX AI from the project's README, source and public GitHub data; it may contain mistakes.

Read the original README https://github.com/larksuite/cli#readme

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