AutoClaw
An AI work agent across desktop, browser, and chat
What it does
AutoClaw is a desktop AI agent for multi-step work across files, browsers, office documents, web apps, and IM. Give it a goal, let it operate tools and coordinate agents, then get the finished work back in the same conversation. GLM-5.3 is built in.
AutoClaw is an out-of-the-box AI assistant with GLM-5.3-Flash now live and 50+ built-in skills for documents, data analysis, browser automation, and IM workflows.
New users register & log in to get 100‑million GLM‑5.3‑Flash tokens, worth $12 Core Capabilities What AutoClaw Can Do AutoClaw brings an AI assistant, office automation, browser automation, and IM workflows into one desktop app. Instead of configuring complex workflows or writing scripts first, you describe the goal and let AutoClaw operate tools, files, browsers, and built-in skills step by step. Generate Word, Excel, PPT, reports, meeting notes, charts, and structured documents with 50+ built-in skills. It helps operations, sales, project managers, and teams handle repetitive documentation work faster. Across Telegram, Instagram posts, Substack long-form, X (Twitter) threads, and TikTok…from autoclaw.z.ai
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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