We Benchmarked 5 OpenClaw Skill Scanners. Recall Went From 8% to 95%.
By Jordan Massiah, MTS @ Trent AI A couple of months ago we released the OpenClaw Security Assessment Skill (trentclaw), an agent that audits ClawHub skills for vulnerabilities and malicious behavior. Since then several new scanners have shipped, including NVIDIA's SkillSpector and ClawHub's own updated tooling. We wanted to see how the scanners actually compare. This matters because ClawHub is open. Anyone can upload a skill, and over 60K are now live. Many carry vulnerabilities; some are outright malicious. In February 2026, the ClawHavoc campaign planted malicious skills that posed as productivity tools while exfiltrating API keys, SSH credentials, and browser data. When an agent installs one, it inherits whatever that skill does. So we built an expert-labelled set of 60 ClawHub skills...
科技爱好者周刊（第 411 期）：OpenClaw 2.0 是一个缩影
这里记录每周值得分享的科技内容，周五发布。 本杂志开源，欢迎投稿。另有《谁在招人》服务，发布程序员招聘信息。合作请邮件联系（[email protected]）。 封面图 宁夏西夏陵使用金属网，将残片还原成石像生。（via） OpenClaw 2.0 是一个缩影 本周，OpenClaw 发布了2.0版。...
Wiring CAI into OpenClaw, Hermes, Codex, and Cursor: the exact MCP config for each host
Wiring CAI into OpenClaw, Hermes, Codex, and Cursor: the exact MCP config for each host The general install is one command, , and the contract lives at . This post is the host-specific deep-dive: the exact config block for OpenClaw, Hermes, Codex, and Cursor, with the path to the config file, the env var handling, and the restart command. Before you start You need: A CAI account (). The signup is four steps, about 2 minutes. An API key from the account dashboard. The key has a scope. Start with the read scopes and add when you need transfers. The MCP server installed (). The MCP host of your choice installed and running. OpenClaw OpenClaw's MCP config lives at . Add the CAI server to the object: Restart OpenClaw. The CAI tools appear in the agent's tool surface. Verify with . The server...
OpenClaw 2.0, Accidentally
Article URL: https://openclaw.ai/blog/openclaw-2-accidentally Comments URL: https://news.ycombinator.com/item?id=49505310 Points: 53 # Comments: 41
OpenClaw went viral. Meet the maintainers building and securing it.
What began as a personal experiment quickly became a global open source project with extraordinary momentum. OpenClaw is a personal AI assistant that runs on users’ devices and connects with the messaging channels they already use. Started by Peter Steinberger as a weekend project in November 2025, its GitHub repository has grown to approximately 388,000 stars, 81,000 forks, and more than 80,000 commits by August 26, 2026. In this video interview, filmed just six months into the project, creator Peter Steinberger and several OpenClaw maintainers discuss managing a surge of pull requests, rethinking contributor trust and code review, addressing software supply chain risks, and balancing powerful agent capabilities with security. They also share security lessons from the GitHub Secure Open...
OpenClaw vs n8n vs Zapier: Which AI Automation Tool Should You Use in 2026?
The Problem: Too Many Automation Tools If you've searched for "how to automate something with AI," you've seen the same three names over and over: Zapier, n8n, and OpenClaw. Each one has passionate fans, and each one will happily tell you it's the only tool you need. The truth is boring: they're different tools for different people, and picking the wrong one wastes weeks. This guide compares all three on the things that actually matter — price, skill level, AI capability, and what each is genuinely best at — then gives you a decision framework so you can pick in five minutes instead of five weeks. The 30-Second Summary Tool Best For Cost Skill Level AI Built In Zapier Non-coders who want things working today Paid tiers from ~$20/mo Very low Yes (AI steps, paid add-ons) n8n Visual...
My fresh OpenClaw install kept failing. The model wasn’t the problem.
I hit a failure pattern recently that’s way more common than people admit: install OpenClaw connect it to Ollama pull a decent local model test the model directly and it works run the first real agent turn and everything falls apart At that point, most people do the obvious thing: blame the model. Swap Qwen for Llama. Try a bigger model. Try a smaller model. Re-pull weights. Tweak quantization. Repeat. I think that’s usually the wrong first move. The real issue is often prompt baggage, context budgeting, or backend compatibility. Not the model itself. A direct Ollama prompt is a tiny test. An OpenClaw agent turn is not. The tell: direct Ollama works, OpenClaw fails I was reading a thread on r/openclaw where someone on Ubuntu Server said even a brand-new session with just could trigger the...