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Hermes Agent's skill trust model is a four-repo allowlist

So far I've only been running openclaw agents and had a steep learning curve. "self-improvement" became a very attractive term on this journey. So I took a dive into Hermes Agent, the self-improving agent runtime from Nous Research. One of the first things I wanted to understand was a risk: what actually happens when you install a community skill? Skills are code and instructions that the agent will execute, and Hermes pulls them from an open ecosystem. So I read the install path in the source - instead of blindly trusting the docs. What I found is better than I expected in one way and structurally limited in another. What Hermes already has on board Hermes does not install external skills blindly. Every externally-sourced skill goes through a real gate before it lands on disk. In hermes_cli/skills_hub.py , the install flow is: fetch → quarantine → scan → policy decision → install or block-and-audit. The scan lives in tools/skills_guard.py and runs regex-based static analysis for known-bad patterns: secret exfiltration ( curl interpolating $API_KEY / $TOKEN / $SECRET ), reads of credential stores ( ~/.ssh , ~/.aws , ~/.gnupg , ~/.kube , and Hermes's own ~/.hermes/.env ), destructive commands, persistence, and obfuscation. If the scan blocks an install, the quarantined copy is deleted and the event is written to an audit log. This is more than most agent tooling ships with. If you remember the wave of malicious skills that hit competing ecosystems, a chunk of that class of attack would be caught here before anything ran. Someone thought about this. The part that doesn't scale imo The scanner produces a verdict — safe , caution , or dangerous . That verdict is then combined with a trust level to decide whether to install. The trust levels and their policies look like this: INSTALL_POLICY = { # safe caution dangerous " builtin " : ( " allow " , " allow " , " allow " ), " trusted " : ( " allow " , " allow " , " block " ), " community " : ( " allow " , " block " , " bloc

2026-06-07 原文 →
AI 资讯

Supercharge your macOS workspace management with Aerospace - A guide for busy people

Aerospace completely revolutionized my workflow after 15 years of using macOS the way Apple intended. I no longer hunt for apps and windows in Mission Control or drag them around spaces to organize. I can open as many windows as I need and have them all under my fingertips. And instead of swiping around to find one, I instantly teleport to where they are. This incredible software is technically aimed at advanced users. It’s installed from the command line and offers extensive configuration options. For basic use though, you don’t need to configure it at all, and if you have opened the Terminal application before and know what running a command means, you should be good to go. Rest assured, I will not show you how to configure Aerospace with Vim, or show you how to create an elaborate but useless dashboard! Just the essentials to get you started. How to set up Aerospace Aerospace is a menu bar application, but you can’t download it from an App Store or get it as a DMG file. You need a package manager. Go to the Homebrew website and follow the installation guide. Make sure to accurately follow the on-screen instructions. This may include any of the following: A prompt to enter your password. When you type passwords in Terminal, you will not see stars or anything. Just make sure you’re typing the correct one and hit Enter. A prompt to install XCode Command Line Tools . Somewhere around the end of the installation process, you may get a prompt to run some extra commands, which depend on your system. Make sure you run them as instructed. To test if you have correctly installed Homebrew, run which brew in Terminal. If you see a path printed out, like /opt/homebrew/bin/brew , you’re good to go. If not, something has gone wrong. Try searching for other, more focused guides on installing Homebrew. With Homebrew, you can install applications from the Terminal app using the brew command. For Aerospace, you would run the following command: brew install --cask nikitabobko/tap/ae

2026-06-07 原文 →
开发者

I built a free image converter that runs 100% in your browser — no upload, no signup

Hey DEV community! 👋 I built IMGVO — a free image tool that works entirely in your browser. What it does Convert JPG, PNG, WebP, AVIF, HEIC and more Compress images up to 90% without quality loss Crop, resize, rotate, watermark Works offline (PWA) Why I built it Most image tools upload your files to servers. I wanted something private and instant. Tech 100% vanilla JavaScript No backend, no server Works offline as PWA Privacy first No files uploaded to any server. Everything runs locally in your browser. 🆓 Free, no signup required. 👉 Try it: https://imgvo.com Would love your feedback! 🙏

2026-06-07 原文 →
AI 资讯

Road To KiwiEngine #11: Why I’m Building Sovereign AI Instead of Another AI Wrapper

Most AI products today are wrappers. Different interfaces. Different branding. Different marketing. But underneath many of them is the same pattern: centralized models, rented intelligence, recurring dependence, and cloud-first control. The user doesn’t own the intelligence. They lease access to it. I think that creates a dangerous future. AI Is Quietly Becoming Infrastructure We’re moving toward a world where AI won’t just help write emails or generate images. It will: operate businesses, manage workflows, coordinate logistics, assist with infrastructure, analyze systems, monitor environments, and increasingly act as operational infrastructure. That changes the stakes dramatically. If AI becomes operational infrastructure, then ownership matters. Control matters. Resilience matters. And right now, most users have very little of any of those things. The Problem With Generalized Intelligence One of the biggest issues I see in modern GenAI is overgeneralization. We’re trying to build one giant intelligence that does everything: coding, marketing, legal reasoning, architecture, writing, support, psychology, operations, and research. The results can be impressive. But also unreliable. Hallucinations happen because the systems are stretched across too many domains simultaneously. The broader the intelligence becomes, the harder consistency becomes. That’s why I’ve become increasingly interested in specialized AI systems. AI Should Work Like A Workforce Instead of one giant model pretending to know everything, I believe AI should operate more like a coordinated workforce. Specialized agents. Focused responsibilities. Defined operational boundaries. For example: a development agent, an infrastructure agent, a security agent, a documentation agent, a research agent, a support agent, a creative writing agent. Each one optimized for a specific domain. Each one independently updateable. Independently replaceable. Independently trainable. Not one brain. Many experts. Local-Firs

2026-06-06 原文 →
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