This repository is a comprehensive, Jekyll-based static site serving as the official tutorial for OpenClaw, an open-source AI agent gateway. It provides a structured, multi-chapter guide (15 chapters + 15 appendices) covering installation, configuration, multi-platform integration (Feishu, WeChat, DingTalk, etc.), automation, and practical use cases for building AI agents. The site includes a polished UX with dark/light mode, scroll-spy navigation, reading progress bar, and a full-text search index. Beyond documentation, the repo contains a substantial collection of automation scripts (markdown-to-docx conversion, image uploading, CSDN auto-publishing, formatting fixes), example skills (JavaScript templates for custom skills), configuration templates (multi-agent, multi-model, Feishu integration), and GitHub Actions for CI/CD (Jekyll build, issue processing, content sync). The repository is actively maintained, with a clear version baseline (v2026.6.8) and frequent updates. While primarily a documentation project, the inclusion of reusable scripts, skill templates, and a well-crafted Jekyll layout makes it valuable for developers building similar documentation sites or OpenClaw-adjacent tools. The hybrid nature is evident: it serves as both a reference manual and a toolkit of reusable components for the OpenClaw ecosystem.
This repository is a curated directory/registry of 5,300+ community-built skills for OpenClaw, an AI agent platform. It is not a software application — it contains no runtime code, no API, and no executable logic. Instead, it is a structured catalog of markdown files organized into 30+ categories (DevOps, Search & Research, Coding Agents, etc.), where each entry links to a skill hosted on ClawHub (OpenClaw's public skills registry). The repo functions as a discovery and navigation layer: users browse categories to find skills, and contributors submit new skills via pull requests validated by a CI workflow. The repository also documents filtering criteria (excluding spam, duplicates, low-quality, crypto, and malicious entries), security considerations (VirusTotal scanning partnership), and contribution guidelines. While it shares some characteristics with a data_research repo (structured metadata, no application code), it is best classified as a curated content registry — the 'application' label applies only in the sense that it is not a data pipeline or research project. Key patterns include a consistent category taxonomy, a PR validation workflow, and documented quality gates. The main risks are link rot (5,300+ external links with no automated checking), quality variance across entries, and the manual effort required to maintain a list at this scale.
This repository is a curated community collection of 42 real-world use cases for OpenClaw (an AI agent framework), organized as markdown documentation. It is NOT a data pipeline, application, or research codebase itself — rather, it's an 'awesome list' style knowledge base documenting how practitioners use OpenClaw for tasks spanning social media automation, content pipelines, infrastructure management, personal productivity, research, and finance. Each use case file describes a workflow pattern, required skills/plugins, setup prompts, and architectural insights. The repo serves as a pattern catalog for agent-based automation. Classification as 'data_research' reflects the content's focus on data/engineering workflows (RAG, ETL, research pipelines, analytics), though the repo itself contains only documentation, not executable code or data.