FAQ
This page answers the most common questions from both new and experienced OpenClaw users.
Basic Concepts
Q: What is OpenClaw? How is it different from ChatGPT?
A: OpenClaw is an open-source autonomous AI agent platform that runs on your own machine. Key differences from ChatGPT:
| Feature | ChatGPT | OpenClaw |
|---|---|---|
| Where It Runs | OpenAI cloud | Your local machine |
| Data Control | OpenAI owns it | You own it |
| Autonomous Actions | Conversation only | Can perform tasks (send emails, control smart home, etc.) |
| Multi-Platform | ChatGPT interface only | 20+ messaging platforms (Telegram, Discord, etc.) |
| Extensibility | Limited GPTs | 13,000+ ClawHub skills |
| Cost | Monthly subscription | Open-source and free (you pay for LLM API usage) |
Q: Is OpenClaw free?
A: OpenClaw itself is open-source and free (MIT license). However, you are responsible for:
- LLM API costs — Using cloud models like Claude or GPT requires payment. Using Ollama with local models is free.
- Messaging platforms — Most are free (Telegram Bot, Discord Bot, etc.); a few may have costs.
- Hardware — Your own computer or server.
Typical monthly costs:
| Usage Level | Estimated Monthly Cost |
|---|---|
| Light (a few conversations per day) | $5-15 |
| Moderate (daily assistant) | $15-50 |
| Heavy (multi-agent + automation) | $50-200+ |
| Fully local (Ollama) | $0 (electricity aside) |
Q: What does "Raising Lobsters" mean?
A: This is OpenClaw's nickname in Asian communities. "Claw" refers to a lobster's claw, and OpenClaw's mascot Molty is a lobster. Users liken the process of configuring and training an OpenClaw agent to "raising a lobster" — you feed it (SOUL.md configuration), train it (memory accumulation), and care for it (maintenance and updates).
Q: Do I need to know how to code to use OpenClaw?
A: Basic usage does not require programming skills. Installation and setup can be completed by following the step-by-step guides. Day-to-day use simply involves chatting with your agent through a messaging app like Telegram.
Advanced usage (custom skills, API integration, multi-agent deployment) does require some programming knowledge.
Security
Q: Is OpenClaw secure?
A: OpenClaw's design is secure, but misconfiguration can create serious risks. Known security issues include:
- CVE-2026-25253: Gateway remote code execution vulnerability (patched)
- ClawHavoc: 2,400+ malicious skills planted in ClawHub (cleaned up)
- 30,000+ instances compromised due to exposed Gateway ports
When configured correctly (bound to localhost, authentication enabled, Podman rootless), OpenClaw is secure. See Security Best Practices for the full guide.
Q: Is my conversation data uploaded anywhere?
A: OpenClaw itself does not upload your data. However, the LLM provider you use will receive your conversation content:
- Cloud LLMs (Claude, GPT, etc.): Your conversations are sent to the provider's servers for processing
- Local LLMs (Ollama): All data stays on your machine, fully offline
If privacy is your top priority, use Ollama with a local model.
Q: Are ClawHub skills safe?
A: ClawHub skills are submitted by community developers and are not guaranteed to be safe. After the ClawHavoc incident, ClawHub added VirusTotal scanning, but automated scanning cannot detect all malicious behavior.
Before installing any skill, complete the checks in the Skill Audit Checklist.
Q: Why is Podman recommended over Docker?
A: The Docker daemon runs with root privileges. If a skill sandbox is breached, an attacker could gain root access to the host machine. Podman's rootless mode does not require root — even if the sandbox is breached, the attacker only gains regular user privileges, dramatically reducing risk.
Installation and Setup
Q: Which operating systems does OpenClaw support?
A:
| Operating System | Support Status |
|---|---|
| macOS 13+ | Fully supported |
| Ubuntu 22.04+ | Fully supported |
| Debian 12+ | Fully supported |
| Fedora 38+ | Fully supported |
| Arch Linux | Community supported (AUR) |
| Windows 11 (WSL2) | Supported (requires WSL2) |
| Windows (native) | Not supported |
| ChromeOS | Not supported |
Q: What are the minimum hardware requirements?
A:
| Component | Minimum | Recommended | Heavy Usage |
|---|---|---|---|
| CPU | 2 cores | 4 cores | 8+ cores |
| RAM | 4 GB | 8 GB | 16+ GB |
| Disk | 2 GB | 5 GB | 20+ GB |
| GPU | Not required | Not required | Nvidia (local LLM acceleration) |
Q: Can I run OpenClaw on a Raspberry Pi?
A: Technically yes, on a Raspberry Pi 4/5 (4GB+ RAM), but performance will be limited. It is only suitable for lightweight use cases (simple notifications and automation) and is not a good fit for large LLMs.
Q: How do I update OpenClaw?
A:
# npm installation
npm install -g @openclaw/cli@latest
# Homebrew installation
brew upgrade openclaw
# Run migration after updating
openclaw migrate
# Verify
openclaw doctor
LLMs and Models
Q: Which LLMs does OpenClaw support?
A: All major LLM providers are supported:
| Provider | Models | Best For |
|---|---|---|
| Anthropic | Claude Opus 4.6, Sonnet 4.5 | General conversation, complex reasoning |
| OpenAI | GPT-5.2 Codex, GPT-4.1 | Code generation, general conversation |
| Gemini 2.5 Pro | Multimodal, long context | |
| DeepSeek | DeepSeek-V3 | High value for the cost |
| Ollama (local) | Llama 3.3, Qwen 2.5, Mistral | Offline use, privacy-first |
| Groq | Various open-source models | Ultra-low latency |
Q: Which model is best?
A: It depends on your needs:
- Best general conversation: Claude Opus 4.6
- Best code generation: GPT-5.2 Codex
- Best value: DeepSeek-V3 or Claude Sonnet 4.5
- Best privacy: Ollama + Llama 3.3 (fully local)
- Lowest latency: Groq
We recommend configuring multiple models and using the LLM Router to automatically route by task type.
Q: Can I use multiple LLMs at the same time?
A: Yes. OpenClaw's LLM Router supports routing different task types to different models. For example: code tasks go to GPT-5.2, conversations go to Claude, and simple tasks go to a local model.
Skills and ClawHub
Q: Which skills are recommended?
A: See Top 50 Must-Have Skills for a comprehensive ranking with category recommendations and security ratings.
Q: How do I develop my own skills?
A: A skill is essentially a Node.js or Python program that conforms to the OpenClaw manifest format. The basic steps:
- Create a
manifest.yamldeclaring skill metadata and permissions - Write the main logic (
index.jsormain.py) - Test locally
- Publish to ClawHub
See MasterClass Module 3: Skills System for a complete walkthrough.
Q: Can skills access my computer?
A: Skills run in container sandboxes and cannot access your computer by default. Skills must declare required permissions (network, filesystem, shell, etc.) in their manifest.yaml, and you can further restrict access via permissions.override.yaml.
Messaging Platforms
Q: Can I connect multiple messaging platforms at once?
A: Yes. This is one of OpenClaw's core features. You can simultaneously connect Telegram, Discord, WhatsApp, Slack, LINE, and more, all handled by the same agent.
Q: Does the agent share memory across platforms?
A: Yes. The memory system is unified. Regardless of which platform a message comes from, the agent has access to the full memory.
Q: Can I set different response styles for different platforms?
A: Yes. In your SOUL.md, you can define platform-specific behavior:
## Platform-Specific Behavior
- Telegram: Keep replies short, use emoji
- Slack: Professional tone, use Markdown formatting
- Discord: Casual style, humor is fine
Memory and SOUL.md
Q: What is SOUL.md?
A: SOUL.md is a Markdown file that defines your agent's personality, behavioral rules, safety boundaries, and daily tasks. It is the agent's "soul" — it determines how the agent thinks and acts.
Q: How long can the agent remember conversations?
A: Theoretically forever. OpenClaw's memory system writes all conversations to the WAL and periodically compacts them into long-term memory. However, during each interaction, the agent can only access recent conversations and relevant long-term memories within the LLM's context window limit.
Q: How do I make the agent forget something?
A:
# Delete a specific conversation
openclaw memory delete --conversation-id "conv_abc123"
# Prune memory older than a date
openclaw memory prune --before "2025-01-01"
# Full reset
openclaw memory reset --confirm
Multi-Agent
Q: What is multi-agent?
A: Multi-agent refers to multiple OpenClaw instances collaborating on tasks. Each agent has a different SOUL.md personality and area of expertise, communicating and coordinating through platforms like Discord or Matrix.
Q: Do I need multiple computers?
A: Not necessarily. You can run multiple OpenClaw instances on the same machine (using different ports and config directories). For performance reasons, large-scale deployments should be distributed across multiple machines.
Cost and Performance
Q: How can I reduce LLM API costs?
A:
- Use LLM Router — Route simple tasks to cheaper models
- Use local models — Ollama is free (just electricity)
- Optimize context — Reduce memory size to lower token consumption
- Set usage limits — Configure monthly caps in your LLM provider's dashboard
- Use DeepSeek — Quality close to Claude/GPT at a fraction of the price
Q: How fast is OpenClaw?
A: Response speed depends primarily on the LLM:
| Scenario | Typical Latency |
|---|---|
| Cloud LLM (simple question) | 1-3 seconds |
| Cloud LLM (complex task + skills) | 3-15 seconds |
| Local LLM (Ollama + GPU) | 2-10 seconds |
| Local LLM (CPU only) | 10-60 seconds |
Community and Learning
Q: Where can I get help?
A:
- Troubleshooting — Immediate answers to common problems
- GitHub Issues — Official bug reports
- Discord #help — Real-time community support
- Reddit r/openclaw — Discussion and historical Q&A search
Q: How can I contribute to OpenClaw?
A: Contributions of any kind are welcome:
- Report bugs — Submit issues on GitHub
- Develop skills — Publish to ClawHub
- Write documentation — Improve the official docs
- Translate — Help with localization
- Answer questions — Help others on Reddit and Discord
- Share showcases — Post your projects on r/openclaw
Q: Is there an official learning course?
A: The MasterClass Course on this site is the most comprehensive learning resource currently available, covering 12 modules from fundamentals to advanced topics.
Further Reading
- What is OpenClaw? — Complete introduction
- Installation Guide — Get started
- MasterClass Course — Structured learning
- Glossary — Term definitions