OpenClaw Multi-Agent Book Writing Skill Released

The multi-agent book writing system built on OpenClaw has been polished and released as a skill. This tool is available at clawhub.ai/chunhualiao/git-repo-to-book.

Key Features

• DeepWiki MCP connection: Integrates with DeepWiki via the Model Context Protocol, allowing the system to access and incorporate information from external knowledge bases during the writing process.
• GLM image generator for better illustration: Uses GLM (likely referring to a Generative Language Model with multimodal capabilities) to create images that complement the text, improving visual content in generated books.
• Budget estimation: Provides cost projections for running the multi-agent system, which is particularly useful given that LLM API calls and image generation can incur expenses.
• Chapter level revision: Enables targeted editing and refinement at the chapter granularity rather than requiring full-book regeneration.

Two chapters have been updated using this skill in the OpenClaw Paradigm Book repository at github.com/chunhualiao/openclaw-paradigm-book. This demonstrates a practical application where the system can maintain and improve existing documentation.

Multi-agent systems for content generation typically involve specialized agents handling different tasks—such as research, writing, editing, and illustration—coordinated through a central controller. The release of this as a "skill" suggests it's designed to be integrated into broader OpenClaw workflows rather than used as a standalone application. For developers working with AI coding agents, tools like this can automate documentation creation, tutorial writing, or technical book drafting by leveraging multiple AI models in a coordinated pipeline.