A comprehensive toolset providing AI agents with direct access to 13+ major internet platforms and social media channels.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install moss-skill-9
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install moss-skill-9 using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Agent Reach?
Agent Reach is a specialized utility designed to give AI agents the ability to perceive and interact with the broader internet. By installing and configuring upstream tools for platforms such as Twitter/X, Reddit, YouTube, GitHub, Bilibili, and WeChat, it allows agents to bypass restrictive wrapper layers and call tools directly. This skill is a foundational component for developers using Openclaw Skills to build sophisticated agents capable of real-time research and multi-platform data extraction.
The tool focuses on maintaining a clean environment by isolating upstream tool repositories and configurations in dedicated directories, ensuring that the user's primary workspace remains unpolluted. It serves as both an installer and a configuration manager, bridging the gap between raw web data and agent-ready input.
Agent Reach Use Cases
- Initial setup of platform access tools for new AI agent environments.
- Automated configuration of social media channels using cookies or browser extraction.
- Real-time research and content retrieval from platforms like LinkedIn, BossZhipin, and XiaoHongShu.
- Monitoring and diagnostic health checks for internet-connected agent tools.
How Agent Reach Works
- The agent triggers the installation process to auto-detect the environment and install core dependencies like Node.js and yt-dlp.
- Upstream tools are cloned into a dedicated hidden directory to keep the workspace clean.
- The user or agent configures specific channels using the doctor command to identify missing credentials or active status.
- Platforms requiring authentication are handled via cookie imports or automatic browser extraction.
- Once configured, the agent executes direct CLI commands or MCP calls to retrieve data from the target platforms.
Agent Reach Setup
To begin using this skill within your environment, follow these installation steps:
pip install https://github.com/Panniantong/agent-reach/archive/main.zip
agent-reach install --env=auto
agent-reach doctor
Run the doctor command frequently to verify channel status and receive instructions for any manual configuration required.
Agent Reach Data Schema & Taxonomy
Agent Reach strictly organizes its data to prevent workspace pollution. The following directory structure is used:
| Path | Description |
|---|---|
/tmp/ |
Used for temporary files such as video subtitles and downloads. |
~/.agent-reach/tools/ |
Stores the repositories and binaries for upstream platform tools. |
~/.agent-reach/ |
Contains configuration files, tokens, and proxy settings. |
~/.config/yt-dlp/ |
Stores YouTube downloader specific configurations. |
Agent Reach Advanced Features
- Direct Model Context Protocol (MCP) integration via mcporter for tools like XiaoHongShu and Douyin.
- Automatic cookie extraction from local Chrome browsers to simplify authentication.
- Multi-platform subtitle and metadata extraction for video content via yt-dlp.
- Stealth browsing capabilities using Camoufox to bypass anti-bot measures on platforms like WeChat.
- Integrated proxy configuration to handle residential IP requirements for sensitive search tasks.
SKILL.md
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