The open‑source Feishu CLI surged to over 10,000 GitHub stars within 47 days, outpacing rival office‑platform CLIs, thanks to its three‑layer command architecture, built‑in Skill system, and seamless integration with AI agents that can automate full‑cycle office workflows.
This article introduces remote-claude, an open‑source tool that lets you monitor and command Claude Code via a Feishu bot on your mobile device, detailing installation, Feishu bot setup, and step‑by‑step usage to enable hands‑free AI coding.
This guide walks you through installing the open‑source Feishu CLI, configuring it with Claude Code, and using the resulting SKILL to let an AI agent interact with Feishu messaging, cloud docs, calendars, and other services for automated workflows.
The article introduces lark‑cli, the official open‑source Feishu command‑line tool that bundles over 200 curated commands across 11 business domains and 19 ready‑to‑use Agent Skills, explains its three‑layer architecture, dual Bot/User identity model, security safeguards, and step‑by‑step installation for both human users and AI agents.
OpenClaw v2026.3.7 brings webhook compatibility fixes, private‑message typing feedback, a 33% token‑saving prompt‑cache, smarter model routing, seamless integration of domestic LLMs such as DeepSeek, Doubao and Qwen, and persistent bindings for Docker deployments, dramatically improving stability, cost efficiency and scalability for enterprise AI agents.
This guide walks you through checking Node.js version, installing OpenClaw via script or npm, configuring personal mode, selecting a model provider and API key, setting up Feishu app credentials and permissions, managing versions, pairing the bot, and using common OpenClaw command‑line tools for operation and troubleshooting.
AutoClaw repackages OpenClaw into a one‑click desktop app that eliminates the multi‑step setup, automatically integrates with Feishu, bundles free GLM models and the new Pony‑Alpha‑2 LLM, and offers a plug‑and‑play skill system for AI‑driven tasks.
AutoClaw wraps the open‑source OpenClaw client, turning a half‑day installation into three simple steps—download, install, and auto‑configure—while adding seamless Feishu integration, support for GLM‑5 and pony‑alpha‑2 models, built‑in skills, and security recommendations for custom skill creation.
This guide walks you through preparing the environment, installing OpenClaw, configuring its onboarding, creating a Feishu custom app, setting up event subscriptions and permissions, and finally pairing the AI agent so it can respond to Feishu messages.
This guide explains how to safely install and containerize OpenClaw using 1Panel, configure a large‑language‑model API (e.g., Alibaba Baileian), and integrate the assistant with Feishu, while highlighting the security risks of exposing a high‑privilege OpenClaw instance to the public internet.
This guide walks you through installing OpenClaw, an AI‑powered computer automation agent, on a macOS machine using Docker, configuring the MiniMax model, setting up the Feishu chatbot plugin, and verifying that the system responds to commands, all with step‑by‑step commands and screenshots.
OpenClaw 2026.3.1 merges over 90 pull requests, introduces Claude adaptive reasoning, faster OpenAI responses via WebSocket, extensive Android node permissions, and Feishu table automation with bilingual UI, while its GitHub star count jumps to 252 K, surpassing React.
This step‑by‑step guide shows how to integrate the OpenClaw AI tool with Feishu by creating a Feishu app, configuring permissions, setting up event subscriptions, adding the Feishu channel in OpenClaw, publishing the app, and testing the AI assistant—all without writing code or hosting a server.
This guide explains why a single AI bot becomes inefficient, introduces OpenClaw’s multi‑agent architecture, and provides a step‑by‑step tutorial—including CLI commands, configuration files, and JSON bindings—to set up isolated agents in different Feishu groups that can collaborate through internal communication channels.
This guide walks you through installing OpenClaw, configuring a Feishu chatbot, adding the Seedance video‑generation skill, and using it to create text‑to‑video or image‑to‑video content, including detailed steps, required permissions, code snippets, and supported AI models.
This guide walks you through installing Docker, Git, and Node.js on a macOS machine, cloning the OpenClaw repository, configuring the gateway token, installing the Feishu plugin, and verifying that the AI agent can be controlled via Feishu messages, all without relying on cloud services.
This free tutorial walks you through installing Clawbot on Windows, macOS or Linux, adding the Feishu plugin, configuring Feishu app credentials, and using Clawbot to generate documents, while highlighting security risks and providing a GitHub reference.
This step‑by‑step guide shows developers how to create a Huawei Cloud development environment, obtain MaaS model tokens, install and configure the OpenClaw AI assistant, integrate it with Feishu via a plugin, set permissions and event callbacks, and finally enable automatic hot‑news push using Python code.
This article explains how a ultra‑lightweight project‑management tool built with Feishu bots and Coze transforms manual, memory‑based to‑do lists into dynamic, rule‑driven workflows, detailing the problem, design principles, three‑layer architecture, implementation steps, and real‑world impact on testing teams.
This guide walks you through building an end‑to‑end n8n workflow that reads topics from a Feishu multi‑dimensional table, generates Xiaohongshu copy and multi‑page covers with AI models, uploads the assets back to Feishu, and updates the table automatically, turning a manual content pipeline into a fully automated factory.
This guide walks through building an n8n workflow that periodically pulls hot articles from multiple RSS sources, enriches each item with a source tag, merges, filters, formats the data, writes it into a Feishu spreadsheet, and finally pushes a notification to a Feishu group, all without manual intervention.
The article reviews various online image placeholder services, highlights challenges such as missing Chinese support and Feishu attachment errors caused by CORS and Content-Length headers, and presents a self‑hosted placeholder tool that resolves these frontend development obstacles.
This guide shows how to combine ELK, DeepSeek’s LLM API, and a Feishu chatbot in Python to automatically collect, analyze, classify, and alert on system logs, using a config file, custom utilities, and a simple historical fault database for intelligent DevOps monitoring.
The article details a complete redesign of Feishu’s cloud‑document‑to‑HTML‑email converter, introducing IoC/DI architecture, inline‑style utilities, and specialized renderers for headings, lists, tables, images, code blocks, and equations, resulting in high‑fidelity Outlook‑compatible emails while shrinking the core code to under three hundred lines.
This guide explains how to export a Feishu knowledge base, configure required Feishu app permissions, set environment variables, and install the Feishu Pages npm package to generate a static website using a Markdown‑based static page generator, supporting CI/CD workflows.
This tutorial explains how to create a Python‑based stock monitoring bot that periodically fetches real‑time prices, compares them with preset thresholds, and sends alerts to a Feishu group via a custom webhook, including step‑by‑step setup and scheduling code.
This guide explains how to set up DBLE's alert webhook to send notifications to various platforms such as WeChat, DingTalk, FeiShu, or a custom URL, including download, installation, configuration file details, and example curl requests for seamless integration.
