Looking for a one‑stop platform that deeply merges frontend development with AI? This community focuses on intelligent frontend tech, offering cutting‑edge insights, practical implementation experience, toolchain innovations, and rich content to help developers quickly break through in the AI‑driven frontend era.
This tutorial walks you through setting up the environment, designing the skill structure, writing the SKILL.md metadata, implementing core Python code, testing locally, and publishing the OpenClaw skill to ClawHub, including best practices for error handling, logging, versioning, and maintenance.
This step‑by‑step tutorial shows how to integrate domestic LLM providers (GLM‑5, GLM‑4.7, GLM‑Flash, Kimi K2.5, DeepSeek, Qwen3‑Coder‑Next, BGE‑M3) into OpenClaw, define model routing, create dedicated controller, writer and coder agents, and run a complete multi‑agent workflow.
This guide outlines a role‑based selection strategy for building a fully domestic OpenClaw model stack, explains common pitfalls when replacing foreign models, details why specific Chinese models fit each role, presents three balanced configurations, and offers a step‑by‑step migration plan.
This guide walks you through twelve concrete configuration techniques—defining the AI's soul, identity, user profile, multi‑agent roles, toolset, memory, error logging, permissions, skills, parallel instances, security, and daily training—to transform OpenClaw from a static tool into a continuously evolving, employee‑like assistant.
This article documents the end‑to‑end process of using Lanhu MCP to convert UI design files into HTML/CSS, covering environment setup, installation, Cursor integration, common errors such as Python 3.13 incompatibility and HTTP 418 responses, and practical work‑arounds when the core API is blocked.
The article examines the shift from Vibe Coding to Agentic Engineering, showing that overloading AI with too many tools confuses it, and argues that developers must evolve from code writers to AI orchestrators who guide and supervise intelligent agents rather than merely issuing commands.
The article proposes a hybrid architecture where Kimi Claw serves as the primary knowledge and search hub while a self‑hosted OpenClaw node supplements it for intranet security and multi‑model experiments, detailing scenarios, data boundaries, step‑by‑step implementation, and model‑tool selection.
The article proposes a hybrid solution for individual developers and small teams where MaxClaw handles everyday multi‑agent tasks while a self‑hosted OpenClaw instance is used for model experiments and high‑privilege operations, covering architecture, deployment steps, cost tactics, and security best practices.
This guide explains what Cursor Cloud Agents are, how to access them via the editor, web UI, or third‑party integrations, outlines three typical scenarios, walks through GitHub repository linking, troubleshooting steps, a quick‑start checklist, and details the Cloud Agents API for automated workflows.
The latest Oh-My-OpenCode Agent introduces intelligent auto‑scheduling that lets users describe requirements in natural language, automatically selects the appropriate expert Agent—whether for code exploration, implementation, architecture design, QA, or UI design—and streamlines complex development workflows with concrete examples, best‑practice tips, and troubleshooting guidance.
