lark-event

Name: lark-event
Availability: InStock
Author: chenguojun06-star

Consume real-time Lark events as NDJSON streams with jq filtering.

1|2|Updated Jan 21, 2026

Search Tags:#automation #webhook #chatbot #feishu #lark #ndjson #event streaming

Ready to run

npx skills add https://github.com/chenguojun06-star/fz66666 --skill lark-event-chenguojun06-star

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: lark-event
Source: https://github.com/chenguojun06-star/fz66666/tree/main/.agents/skills/lark-event
Command: npx skills add https://github.com/chenguojun06-star/fz66666 --skill lark-event-chenguojun06-star

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps AI agents and applications reliably consume real-time Lark/Feishu events without building custom webhook listeners or event stream handling logic from scratch.

Core Features & Use Cases

Real-Time Event Consumption: Stream Lark events as NDJSON for message handling, reactions, chat changes, and bot workflows.
Schema-Driven Processing: Inspect available event keys and schemas, then apply precise jq filtering and field extraction.
Use Case: Build a Lark bot that monitors incoming messages, processes selected conversations, and triggers automated responses or business workflows.

Quick Start

Use the lark-event skill to consume incoming Lark messages for a bot and return only the relevant event content.

Frequently Asked Questions about lark-event

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

FAQPage Schema

How do I consume real-time Lark events for an automated chatbot workflow?▼

To consume real-time Lark events, you use lark-cli event commands to stream incoming messages and chat changes as NDJSON. This allows automated chatbot workflows to process events directly without building custom webhook listeners.

What is the best way to filter Lark message streams for specific event types?▼

The best way to filter Lark message streams is by applying jq filtering to the NDJSON event stream. You can inspect available event keys and schemas first, then extract precise fields to isolate specific reactions or chat membership changes.

Can I use lark-cli to monitor chat membership and message reactions continuously?▼

Yes, lark-cli supports long-running event subscribers that continuously monitor chat membership tracking and reaction handling. It manages the subprocess lifecycle to keep the real-time event streaming active for automated collaboration workflows.

Do I need to build a custom webhook listener to process Feishu bot messages?▼

No, you do not need to build a custom webhook listener to process Feishu bot messages. This Skill uses schema-driven processing and NDJSON streaming to handle incoming events directly, bypassing the need for custom webhook infrastructure.

How do I inspect available event schemas before processing a Lark event stream?▼

You inspect available event schemas by using the schema inspection capabilities of the lark-cli event commands. This reveals the available event keys, allowing you to apply precise jq filtering and field extraction before processing the NDJSON stream.