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meet scribe! it's like google docs, but for markdown when doing anything with ai, it was a pain in the ass to collab on plan docs & copy for emails/blogs. scribe solves that, it's the best way for humans & agents to collaborate on markdown fully multiplayer. supports code...

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Nick Khami

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30,794 görüntüleme • 4 gün önce •via X (Twitter)

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Three skills I use every day in Claude Code and Codex to solve my hardest problems: 1️⃣ /agent-watchdog When I have one agent like Codex working on a task and I don't fully trust it's going to do everything right, I'll open up another one like Claude Code and tell it to watchdog the Codex thread. You can copy the Codex deep link into Claude Code and it'll look at the prompt you sent, watch the Codex thread until it's done, then compare the Codex solution to how it was planning to solve it and automatically fix anything that Codex missed. It can also test the work of the other agent end-to-end. Similar to the idea of OpenRouter's new Fusion feature, I've definitely found that two models thinking through a problem and checking each other's work can be wildly more impactful than just one. 2️⃣ /plan-arbiter Similar ideas as /agent-watchdog - but with this one you have both make plans, compare plans, negotiate the differences, and make a final plan to execute. I find Claude Code is better at writing plans, but Codex is faster and cheaper to execute on them. Then I usually have Claude Code watchdog the Codex work and fix anything that was missed. 3️⃣ /read-the-damn-docs One thing that drives me crazy with coding agents is they're so reluctant to look up docs. They'll just guess and guess and guess at the right API surface for things, or the right solution to an integration of two things. Once I explicitly tell it to look up the docs, it says "Oh, I see the answer," and it fixes the problem. So I made the /read-the-damn-docs skill. Add it and your agents will know when and how to do efficient web searches to look up docs for the types of problems you really should look up docs for. All of these are totally open source over on my GitHub. If you try them, let me know your feedback. Will link to them below:

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Guohao Li 🐫

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Ansh Rathod

10,835 görüntüleme • 2 yıl önce

My favorite way of interacting with Claude Code is to have it generate static HTML files as outputs (reports, explorations, code structure, mockups etc.) I wanted to iterate on the file by commenting in browser and having Claude update the output live. So, I built this Claude Skill👇 How it works: - Install Claude Code skill (ask it to clone repo) - Build an HTML page for anything (e.g. research coding agents and generate HTML report) - Ask it to make the page interactive That's it. CC will launch a localhost server and allow you to then leave comments on the page itself and once it updates, will give you a tour of changes. It's like Google Docs kind of comments/iteration but for HTML pages.
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My favorite way of interacting with Claude Code is to have it generate static HTML files as outputs (reports, explorations, code structure, mockups etc.) I wanted to iterate on the file by commenting in browser and having Claude update the output live. So, I built this Claude Skill👇 How it works: - Install Claude Code skill (ask it to clone repo) - Build an HTML page for anything (e.g. research coding agents and generate HTML report) - Ask it to make the page interactive That's it. CC will launch a localhost server and allow you to then leave comments on the page itself and once it updates, will give you a tour of changes. It's like Google Docs kind of comments/iteration but for HTML pages.

Paras Chopra

215,134 görüntüleme • 2 ay önce

AI agents are a real paradigm shift You can literally make your computer work for you to do any task. All I've used is: - Replit to get it running - Browser Use (free & open source) - Google AI Studio for the API - DeepSeek R1 to implement it (I'm not paying $200 for ChatGPT sorry) Here the AI agent fetches information on its own and reuses it to write new content. But you can use it for literally any industry. Run it once or schedule it at regular intervals... you're in total control And it's nothing like automating on Make or Zapier: AI agents adapt to every situation and can handle far more complex scenarios.
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AI agents are a real paradigm shift You can literally make your computer work for you to do any task. All I've used is: - Replit to get it running - Browser Use (free & open source) - Google AI Studio for the API - DeepSeek R1 to implement it (I'm not paying $200 for ChatGPT sorry) Here the AI agent fetches information on its own and reuses it to write new content. But you can use it for literally any industry. Run it once or schedule it at regular intervals... you're in total control And it's nothing like automating on Make or Zapier: AI agents adapt to every situation and can handle far more complex scenarios.

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Working on a detailed prompt? 📝 Press Ctrl+X to open and edit the prompt in your preferred editor like Google Antigravity for example. When you are done, your prompt will be waiting for you back in Gemini CLI 🪄
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Gemini CLI

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This is one of the coolest open-source AI agent projects I've seen in a while: 'Understand Anything' It's a plugin for Claude Code, Codex, OpenCode etc. that analyzes your codebase and turns it into a knowledge base that you can interact with. It explains the codebase to you, rather than showing you the structure. It seems like it's designed for code but I opened my Obsidian vault of podcast highlights in Claude Code, then ran /understand. The result is a knowledge graph that I can search of highlights from 888 podcast episodes and 144K lines of markdown text.
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This is one of the coolest open-source AI agent projects I've seen in a while: 'Understand Anything' It's a plugin for Claude Code, Codex, OpenCode etc. that analyzes your codebase and turns it into a knowledge base that you can interact with. It explains the codebase to you, rather than showing you the structure. It seems like it's designed for code but I opened my Obsidian vault of podcast highlights in Claude Code, then ran /understand. The result is a knowledge graph that I can search of highlights from 888 podcast episodes and 144K lines of markdown text.

Dan McAteer

173,339 görüntüleme • 1 ay önce