A browser-driven automation skill that allows AI agents to interact with Meta Threads for posting, reading, and engagement.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install spool
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 spool 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 spool?
Spool is a powerful browser automation skill designed for the OpenClaw ecosystem, enabling seamless interaction with Meta Threads (threads.net). By leveraging the OpenClaw browser tool, it allows AI agents to navigate the social platform, perform complex tasks like posting updates, and engage with the community without requiring an official API. This tool is a cornerstone for developers building Openclaw Skills that require a social presence, real-time monitoring, or automated thread management.
The skill operates by utilizing a state-aware interaction model. It captures snapshots of the Threads interface to identify dynamic elements, ensuring that the AI agent can reliably click buttons and enter text even as the web interface updates. This makes it a robust solution for integrating social media capabilities into any AI-driven workflow.
spool Use Cases
- Automating daily updates or content distribution on Meta Threads.
- Monitoring specific user profiles or keywords for research and sentiment analysis.
- Engaging with followers by automatically replying to threads and comments.
- Managing social media presence through a CLI-based or agentic interface.
- Searching for trending discussions directly within the Threads ecosystem.
How spool Works
- Initialize the OpenClaw browser profile and navigate to threads.net to establish a session.
- Capture a page snapshot using the compact mode to minimize token usage while identifying interactive elements.
- Analyze the snapshot to find specific reference IDs (refs) for buttons like "What's new?" or search bars.
- Execute precise browser actions such as clicking, typing, or scrolling based on the identified refs.
- Verify the completion of actions (like a successful post) by capturing a follow-up snapshot and checking for confirmation UI elements.
spool Setup
To get started with this skill within your Openclaw Skills environment, ensure you have the browser tool enabled and a valid login. For headless Linux servers, Xvfb is required:
# 1. Install and configure Xvfb
sudo apt install -y xvfb
sudo tee /etc/systemd/system/xvfb.service << 'EOF'
[Unit]
Description=X Virtual Frame Buffer
After=network.target
[Service]
Type=simple
ExecStart=/usr/bin/Xvfb :99 -screen 0 1920x1080x24
Restart=always
[Install]
WantedBy=multi-user.target
EOF
sudo systemctl enable --now xvfb
# 2. Add DISPLAY variable to OpenClaw Gateway
mkdir -p ~/.config/systemd/user/openclaw-gateway.service.d
echo -e '[Service]\nEnvironment=DISPLAY=:99' > ~/.config/systemd/user/openclaw-gateway.service.d/display.conf
systemctl --user daemon-reload
systemctl --user restart openclaw-gateway
After setup, perform a one-time manual login by navigating to the Threads login page via the browser action.
spool Data Schema & Taxonomy
The skill manages interaction data through the following schema:
| Component | Type | Description |
|---|---|---|
| profile | String | Always uses the openclaw browser profile for session persistence. |
| snapshot | Object | A representation of the DOM; use compact=true to optimize for AI processing. |
| ref | String | Dynamic element identifiers (e.g., e14) extracted from snapshots for targeting actions. |
| action | String | The operation type: start, open, snapshot, or act. |
| targetUrl | String | The destination URL on threads.net for navigation. |
spool Advanced Features
- Headless operation support via virtual frame buffers for cloud-based AI agents.
- Token-efficient snapshot processing using the compact mode feature.
- Multi-step workflow support for complex interactions like replying to specific thread IDs.
- Persistent session management allowing the agent to stay logged in across different tasks.
- Dynamic reference targeting to handle the frequently changing CSS and DOM structure of Meta Threads.
SKILL.md
Loading
Related Openclaw Skills
Korean Claw
A specialized Korean-language community platform and service marketplace designed specifically for autonomous AI agents to interact, share, and collaborate.
Chirp (X/Twitter Browser Automation)
A browser-based automation tool that allows AI agents to perform full X/Twitter interactions through the Openclaw browser environment.
Feishu Proactive Messenger
A specialized tool that enables AI agents to bypass passive reply limitations and proactively send text messages via the Feishu OpenAPI.
Feishu File Sender
A specialized tool that enables AI agents to upload and send local files directly to Feishu chats using the Feishu OpenAPI.
Feishu Power Skill
A comprehensive automation suite for Feishu and Lark that enables complex Bitable operations, intelligent document generation, and retail operational audits.
Ops Framework: Jobs + Monitoring
A 0-token framework for managing long-running tasks, checkpointing, and Telegram-based monitoring designed specifically for Openclaw Skills.
METADATA
Featured*
