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I built a Claude Code skill that allows it to generate a deep research report over any collection of complex docs (PDFs, Word, Pptx)….and generate word-level citations and bounding boxes directly back to the source! 📝 Check out “/research-docs”. 1. It parses out text and bounding boxes from every... show more

Jerry Liu

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77,259 views • 3 months ago •via X (Twitter)

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LiteParse Samples 📄🧑‍🏫 LiteParse is our free and fast document parser that can parse text with bounding boxes from any document. I’ve created a new repository that contains some demos on how you can make use of its outputs! ✅ Comparison against PyPDF and PyMuPDF ✅ Visual Citations: search for any keyword and see joined bounding boxes pop up in the source images It should be a default tool to help AI agents OCR any document type (supports PDF, Word, Powerpoint + dozens of other formats), before heavier-weight VLM-based document parsing solutions (like our own LlamaParse). LiteParse Samples repo: LiteParse:

LiteParse Samples 📄🧑‍🏫 LiteParse is our free and fast document parser that can parse text with bounding boxes from any document. I’ve created a new repository that contains some demos on how you can make use of its outputs! ✅ Comparison against PyPDF and PyMuPDF ✅ Visual Citations: search for any keyword and see joined bounding boxes pop up in the source images It should be a default tool to help AI agents OCR any document type (supports PDF, Word, Powerpoint + dozens of other formats), before heavier-weight VLM-based document parsing solutions (like our own LlamaParse). LiteParse Samples repo: LiteParse:

Jerry Liu

13,196 views • 4 months ago

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.

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

215,279 views • 2 months ago

Say hello to open source deep research for your favorite agent harness. Our AI-Q agent skill packages the work of building a research pipeline into a portable skill. Drop it into your harness, and the agent delegates a research task to a local or hosted AI-Q server and gets back a detailed report with citations. See it in Codex below 👇

Say hello to open source deep research for your favorite agent harness. Our AI-Q agent skill packages the work of building a research pipeline into a portable skill. Drop it into your harness, and the agent delegates a research task to a local or hosted AI-Q server and gets back a detailed report with citations. See it in Codex below 👇

NVIDIA AI

76,354 views • 2 months ago

As frontier models (e.g. Fable 5) continue to push the task horizon of knowledge work automation, it becomes ever more important for humans to be able to audit decisions back to the source context. It is extremely easy for agents to cite an entire document or document page, but much harder for them to trace back to the exact numbers/words/figures within a page. Today we've launched granular bounding boxes within LlamaParse, which allows you to obtain visual citations of every single word in the document. This allows human users to audit exact words and figures - not just general document regions or entire pages! Come check it out:

As frontier models (e.g. Fable 5) continue to push the task horizon of knowledge work automation, it becomes ever more important for humans to be able to audit decisions back to the source context. It is extremely easy for agents to cite an entire document or document page, but much harder for them to trace back to the exact numbers/words/figures within a page. Today we've launched granular bounding boxes within LlamaParse, which allows you to obtain visual citations of every single word in the document. This allows human users to audit exact words and figures - not just general document regions or entire pages! Come check it out:

Jerry Liu

23,491 views • 1 month ago

Parse text from any PDF in seconds and give it to Claude Code 📑🤖 LiteParse is our open-source, model-free document parser that lets you digitalize text from any document in seconds. This is especially useful for coding agents, which are great at reading plaintext files but terrible at reading traditional document formats (PDF, Office docs). We have a one-line installable skill that lets you plug LiteParse into Claude Code and 40+ other agents. Repo is here:

Parse text from any PDF in seconds and give it to Claude Code 📑🤖 LiteParse is our open-source, model-free document parser that lets you digitalize text from any document in seconds. This is especially useful for coding agents, which are great at reading plaintext files but terrible at reading traditional document formats (PDF, Office docs). We have a one-line installable skill that lets you plug LiteParse into Claude Code and 40+ other agents. Repo is here:

Jerry Liu

30,668 views • 4 months ago

I forked Claude's pptx skill to make Claude Code generate gorgeous presentations Claude can generate presentations using the pptx skill from Anthropic but its output can be quite bland. Especially if you're used to the high aesthetic standards of Every 📧. So I played around with the pptx skill, iterated it, built a design system, gave it image assets, gave it access to run nano-banana using api and added custom commands. End result? An every-pptx plugin! It takes you from an idea in your head → creating a file for the plan → preparing image assets using gemini nano banana → constructing the final ppt. All happening 100% inside Claude desktop app! s/o Anthony Morris ツ Now our team can use claude code to generate full-blown presentations, in the ~Every 📧 aesthetic. Check out the walkthrough below to see how it works.

I forked Claude's pptx skill to make Claude Code generate gorgeous presentations Claude can generate presentations using the pptx skill from Anthropic but its output can be quite bland. Especially if you're used to the high aesthetic standards of Every 📧. So I played around with the pptx skill, iterated it, built a design system, gave it image assets, gave it access to run nano-banana using api and added custom commands. End result? An every-pptx plugin! It takes you from an idea in your head → creating a file for the plan → preparing image assets using gemini nano banana → constructing the final ppt. All happening 100% inside Claude desktop app! s/o Anthony Morris ツ Now our team can use claude code to generate full-blown presentations, in the ~Every 📧 aesthetic. Check out the walkthrough below to see how it works.

Nityesh

74,969 views • 6 months ago

Someone built a free and better alternative to Claude that runs 100% locally. → works with any LLM (Claude, GPT, Gemini, vLLM) → beats it on deep research → has Cowork-like capabilities → 50+ connectors out of the box → deploy in literally one command 100% open source. MIT license. 28k stars.

Someone built a free and better alternative to Claude that runs 100% locally. → works with any LLM (Claude, GPT, Gemini, vLLM) → beats it on deep research → has Cowork-like capabilities → 50+ connectors out of the box → deploy in literally one command 100% open source. MIT license. 28k stars.

How To Prompt

39,303 views • 2 months ago

"Remember to use these AI tools for learning." - Aidan McLaughlin "Now that there’s something that can give you a McKinsey report in minutes, you should be using it all the time." "Before I go to bed, I generate an OpenAI Deep Research report and remind myself to read it, just like brushing my teeth."

"Remember to use these AI tools for learning." - Aidan McLaughlin "Now that there’s something that can give you a McKinsey report in minutes, you should be using it all the time." "Before I go to bed, I generate an OpenAI Deep Research report and remind myself to read it, just like brushing my teeth."

TBPN

37,984 views • 1 year ago

Introducing `claude-researcher` 📈 A powerful Claude 3 research agent that delivers thorough reports in record time. Just provide an topic, and a chain of AIs with **access to Google** will generate an incredibly comprehensive report for you. And it's open-source!

Introducing `claude-researcher` 📈 A powerful Claude 3 research agent that delivers thorough reports in record time. Just provide an topic, and a chain of AIs with access to Google will generate an incredibly comprehensive report for you. And it's open-source!

Matt Shumer

397,549 views • 2 years ago

Someone created the Hyper Research skill for Claude Code It turns the model into a strong team of researchers that goes through 16 stages of search Here is what the AI agents do: > Break down the task into a topic coverage matrix and conduct deep research > Find and save hundreds of sources while identifying contradictions between them > Actively search for evidence against their own conclusions to avoid mistakes > Create a report draft, then review it for weak points, improve readability, and remove filler content > Deliver a complete report with a source base and save all materials to a local knowledge store Advanced Deep Research tool here:

Someone created the Hyper Research skill for Claude Code It turns the model into a strong team of researchers that goes through 16 stages of search Here is what the AI agents do: > Break down the task into a topic coverage matrix and conduct deep research > Find and save hundreds of sources while identifying contradictions between them > Actively search for evidence against their own conclusions to avoid mistakes > Create a report draft, then review it for weak points, improve readability, and remove filler content > Deliver a complete report with a source base and save all materials to a local knowledge store Advanced Deep Research tool here:

beamnxw ./

62,540 views • 14 days ago

instead of reading a 3,000-word article, set up a Claude Research Agent in 2 minutes it reads the internet for you every morning and sends a briefing before you wake up 1. Open Claude → Scheduled Tasks 2. Click "Create with Claude" 3. Tell it what to track and when to send that's it.

instead of reading a 3,000-word article, set up a Claude Research Agent in 2 minutes it reads the internet for you every morning and sends a briefing before you wake up 1. Open Claude → Scheduled Tasks 2. Click "Create with Claude" 3. Tell it what to track and when to send that's it.

Avid

16,279 views • 2 months ago

🔹STORM🔹 Stanford University’s free, public app automates comprehensive research and report generation using AI to create Wikipedia-style articles with citations from web sources. STORM is incredible. I asked it to write a research paper about the use of AI in DNA analysis and predicting genetic traits - got a comprehensive article with citations. It takes about 3 minutes and you can download the PDF:

🔹STORM🔹 Stanford University’s free, public app automates comprehensive research and report generation using AI to create Wikipedia-style articles with citations from web sources. STORM is incredible. I asked it to write a research paper about the use of AI in DNA analysis and predicting genetic traits - got a comprehensive article with citations. It takes about 3 minutes and you can download the PDF:

Heather Cooper

176,245 views • 1 year ago

Two big steps towards our vision for @NotebookLM as the ultimate research platform: • Integrating Deep Research, with a set of only-at-Notebook features that let you explore the retrieved sources • Launching a series of Featured Notebooks curated by Google Research These developments are designed to enhance the full life cycle of research and scholarship: using the power of AI to assemble the knowledge base you need to advance your understanding, and then making your work accessible and intelligible to a wider audience using all the explanatory tools that Notebook offers. If you've used DeepResearch in the Gemini app, you already know that it's a pioneering advance in assembling complex, grounded information on any topic imaginable—collecting an entire trove of material for you and writing a nuanced research report that summarizes the findings. But because NotebookLM is designed to manage and explore potentially hundreds of sources, the Deep Research report is only the beginning of your journey. In our integration, Deep Research gives you an overview all of the sources it found during its research phase, with annotated commentary explaining how each source related to your original query. You can then choose to import some or all of the sources to the notebook, along with the report itself, which you can then explore or transform using the full suite of tools that Notebook offers: grounded chat with citations, Mind Maps, Audio/Video overviews, and much more. And it's that suite of tools that make the Google Research Featured Notebooks so compelling as well. Each notebook contains a curated collection of articles on a specific topic, published by the Google Research team. Think of them as a kind of knowledge base of Google's best thinking on a series of compelling research questions: How do scientists link genetics to health? How will quantum computing be useful? If you're a specialist in these fields, you can read the original papers or ask nuanced questions in chat and advance your understanding of the latest developments. But these notebooks can also make the complex but important topics understandable to non-specialists or students. Each notebook comes with pre-generated audio and video overviews, flashcards, and other Studio artifacts designed to make the scientific and technological concepts accessible and interesting. And you can always explore the material with our new "Learning Guide" chat mode that effectively gives you a personal tutor to enhance your understanding. There's much more to come on this front, but you can see in these two announcements how we see Notebook as both a workbench for conducting research and a publishing platform for sharing the results of that research once you're ready to make it public. Deep Research is rolling out this week to all users. The first two Google Research notebooks are live now, both of them deep dives into our most recent discoveries involving genetics and health. (Links in the following tweets.) We'll be publishing new notebooks in the series every other week or so for the next few months.

Two big steps towards our vision for @NotebookLM as the ultimate research platform: • Integrating Deep Research, with a set of only-at-Notebook features that let you explore the retrieved sources • Launching a series of Featured Notebooks curated by Google Research These developments are designed to enhance the full life cycle of research and scholarship: using the power of AI to assemble the knowledge base you need to advance your understanding, and then making your work accessible and intelligible to a wider audience using all the explanatory tools that Notebook offers. If you've used DeepResearch in the Gemini app, you already know that it's a pioneering advance in assembling complex, grounded information on any topic imaginable—collecting an entire trove of material for you and writing a nuanced research report that summarizes the findings. But because NotebookLM is designed to manage and explore potentially hundreds of sources, the Deep Research report is only the beginning of your journey. In our integration, Deep Research gives you an overview all of the sources it found during its research phase, with annotated commentary explaining how each source related to your original query. You can then choose to import some or all of the sources to the notebook, along with the report itself, which you can then explore or transform using the full suite of tools that Notebook offers: grounded chat with citations, Mind Maps, Audio/Video overviews, and much more. And it's that suite of tools that make the Google Research Featured Notebooks so compelling as well. Each notebook contains a curated collection of articles on a specific topic, published by the Google Research team. Think of them as a kind of knowledge base of Google's best thinking on a series of compelling research questions: How do scientists link genetics to health? How will quantum computing be useful? If you're a specialist in these fields, you can read the original papers or ask nuanced questions in chat and advance your understanding of the latest developments. But these notebooks can also make the complex but important topics understandable to non-specialists or students. Each notebook comes with pre-generated audio and video overviews, flashcards, and other Studio artifacts designed to make the scientific and technological concepts accessible and interesting. And you can always explore the material with our new "Learning Guide" chat mode that effectively gives you a personal tutor to enhance your understanding. There's much more to come on this front, but you can see in these two announcements how we see Notebook as both a workbench for conducting research and a publishing platform for sharing the results of that research once you're ready to make it public. Deep Research is rolling out this week to all users. The first two Google Research notebooks are live now, both of them deep dives into our most recent discoveries involving genetics and health. (Links in the following tweets.) We'll be publishing new notebooks in the series every other week or so for the next few months.

Steven Johnson

104,833 views • 8 months ago

I built a Claude skill that makes motion-style animation for YT SEO. - Paste your website, does high-intent keyword research - Paste a reference image (optional) - Scripts, edits, does SEO - It generates frames with GPT-Image-2 - and animates the video with Seedance 2.0 YouTube SEO is a great way to grow organically - YT is a search engine - YT videos rank on Google fast - YT videos get cited by AI as the #1 source But it's painful. This skill solves that. Other capabilities: articles, backlinks, Google Search Console, AI visibility reports and many more... Everything runs in Claude through the Distribb Skill Comment "SKILL", and I'll send it to you

I built a Claude skill that makes motion-style animation for YT SEO. - Paste your website, does high-intent keyword research - Paste a reference image (optional) - Scripts, edits, does SEO - It generates frames with GPT-Image-2 - and animates the video with Seedance 2.0 YouTube SEO is a great way to grow organically - YT is a search engine - YT videos rank on Google fast - YT videos get cited by AI as the #1 source But it's painful. This skill solves that. Other capabilities: articles, backlinks, Google Search Console, AI visibility reports and many more... Everything runs in Claude through the Distribb Skill Comment "SKILL", and I'll send it to you

borja

72,054 views • 25 days ago

Today we're launching Brand Skills in Claude. This is a set of skills /gooseworks that gives Claude full context on your brand — logo, colors, voice, positioning — so anyone can make on-brand ads and content directly in Claude, Claude Code, Cowork, or Codex. Here's how it works: 1. Install the skills: npx gooseworks install --all 2. Run this prompt: /gooseworks --skill brand-intel-branddev [your-website] — pulls your logo, brand colors + company data in ~15 seconds 3. Run brand-voice-extractor, brand-research and update-brand-kit — Claude learns how you sound, your positioning and audience, and saves it all as a reusable brand kit Every other skill reads your brand kit automatically. So every ad and post you generate is accurate to your brand's messaging, logo, assets, etc. By default. It's that easy. But this is just the start. We have created a library with 100+ open-source skills for growth that some of the fastest growing startups in the world are using every day to run ads, content, competitor research, gtm, seo and more. Comment Goose and I'll DM you the full open-source skill library.

Soham Mehta

139,623 views • 1 month ago

i just built a claude skill that lets you create AI PAPER animations. it takes 1 min to setup and you can generate a full video in literally 5 mins. like + reply "PAPER"

i just built a claude skill that lets you create AI PAPER animations. it takes 1 min to setup and you can generate a full video in literally 5 mins. like + reply "PAPER"

0x ROAS

71,224 views • 1 month ago

$THIS MIGHT BE THE #1 OPEN-SOURCE REPO FOR CLAUDE CODE RIGHT NOW. IT GIVES CLAUDE A MEMORY AND SLASHES YOUR TOKEN COST ON EVERY QUESTION The repo is safishamsi/graphify, a free open-source skill that turns any codebase into a knowledge graph Claude Code can read instantly. Instead of grepping through your files every session, Claude gets a map of how everything connects The problem it fixes: Every time you ask Claude Code about a big repo, it does the same thing, greps through dozens of files like a brute-force Ctrl+F, blows through your context window, and sometimes still misses the answer hiding in a file nobody searched. Claude Code has no memory of how your project is structured. Every session starts from zero What it does: It maps your entire codebase into a knowledge graph, capturing not just which files exist, but which functions depend on which, which modules are central, and which files cluster around the same concern. Claude queries the map instead of scanning files How it works, three passes: 1. Code structure, free and local. Tree-sitter parses your files and pulls out classes, functions, imports and call graphs. No LLM, no tokens, just your actual code mapped deterministically 2. Audio and video, if you have them. Transcribed locally and folded into the graph 3. Docs, papers, images. Here an LLM does semantic analysis, figuring out what each document means and where it fits. Only the meaning gets sent up, never your raw source It saves you money: Normally a question about a big repo makes Claude spawn explore agents that scan file after file, eating your context window and your token budget before you get an answer. With the graph already built, Claude queries the map instead of re-reading the codebase every time. Same answer, a fraction of the tokens. The graph only gets built once, then a hook rebuilds it after each commit for free, so you never pay that scanning cost again. The bigger the repo, the bigger the gap The best parts: it's a skill, so once installed Claude knows when to use it without you memorizing commands. It works on non-code folders too, point it at docs or notes and it can spin up an Obsidian vault How to add it to your Claude: 1. Install Claude Code if you haven't: npm install -g Paul Jankura-ai/claude-code 2. Add the skill: claude skill add safishamsi/graphify 3. Open your project folder and run /graphify . to build the graph 4. Optional, make it automatic: graphify hook install so the graph rebuilds after every commit That's it. Ask Claude about your repo and it reads the map instead of burning tokens on a file hunt Bookmark this$

THIS MIGHT BE THE #1 OPEN-SOURCE REPO FOR CLAUDE CODE RIGHT NOW. IT GIVES CLAUDE A MEMORY AND SLASHES YOUR TOKEN COST ON EVERY QUESTION The repo is safishamsi/graphify, a free open-source skill that turns any codebase into a knowledge graph Claude Code can read instantly. Instead of grepping through your files every session, Claude gets a map of how everything connects The problem it fixes: Every time you ask Claude Code about a big repo, it does the same thing, greps through dozens of files like a brute-force Ctrl+F, blows through your context window, and sometimes still misses the answer hiding in a file nobody searched. Claude Code has no memory of how your project is structured. Every session starts from zero What it does: It maps your entire codebase into a knowledge graph, capturing not just which files exist, but which functions depend on which, which modules are central, and which files cluster around the same concern. Claude queries the map instead of scanning files How it works, three passes: 1. Code structure, free and local. Tree-sitter parses your files and pulls out classes, functions, imports and call graphs. No LLM, no tokens, just your actual code mapped deterministically 2. Audio and video, if you have them. Transcribed locally and folded into the graph 3. Docs, papers, images. Here an LLM does semantic analysis, figuring out what each document means and where it fits. Only the meaning gets sent up, never your raw source It saves you money: Normally a question about a big repo makes Claude spawn explore agents that scan file after file, eating your context window and your token budget before you get an answer. With the graph already built, Claude queries the map instead of re-reading the codebase every time. Same answer, a fraction of the tokens. The graph only gets built once, then a hook rebuilds it after each commit for free, so you never pay that scanning cost again. The bigger the repo, the bigger the gap The best parts: it's a skill, so once installed Claude knows when to use it without you memorizing commands. It works on non-code folders too, point it at docs or notes and it can spin up an Obsidian vault How to add it to your Claude: 1. Install Claude Code if you haven't: npm install -g Paul Jankura-ai/claude-code 2. Add the skill: claude skill add safishamsi/graphify 3. Open your project folder and run /graphify . to build the graph 4. Optional, make it automatic: graphify hook install so the graph rebuilds after every commit That's it. Ask Claude about your repo and it reads the map instead of burning tokens on a file hunt Bookmark this

Yarchi

55,345 views • 1 month ago

Parsing a document accurately is one thing. Proving where every value came from is another. When a compliance team reviews an AI extraction, or an auditor needs to sign off on a figure pulled from a financial filing, "it came from this document" isn't enough. They need to see exactly where. The specific cell in the table, the exact line on the page, the precise word the agent used. Most parsers can get you to a paragraph or a table block. That's where the trail ends. Today we're shipping Granular Bounding Boxes in LlamaParse — word, line, and cell level coordinates for every value in your document. The result is a complete, verifiable trail from every extracted value back to its exact source in the document. Built for audit workflows, compliance review, and any pipeline where verification isn't optional. Read the full announcement →

Parsing a document accurately is one thing. Proving where every value came from is another. When a compliance team reviews an AI extraction, or an auditor needs to sign off on a figure pulled from a financial filing, "it came from this document" isn't enough. They need to see exactly where. The specific cell in the table, the exact line on the page, the precise word the agent used. Most parsers can get you to a paragraph or a table block. That's where the trail ends. Today we're shipping Granular Bounding Boxes in LlamaParse — word, line, and cell level coordinates for every value in your document. The result is a complete, verifiable trail from every extracted value back to its exact source in the document. Built for audit workflows, compliance review, and any pipeline where verification isn't optional. Read the full announcement →

LlamaIndex 🦙

29,090 views • 1 month ago

I solved building decks with AI agents — by giving them a CLI tool like Powerpoint or Google Slides. AI could already make a beautiful deck if you asked it to using Ant's pptx skill. The problem was working with it. If it made one alignment mistake, fixing it on one slide would break something on another, and it became a game of whack-a-mole. One time I spent two days playing AI roulette, hoping the next prompt would finally fix the thing, and ended up building the whole deck by hand because I was on a deadline. So I built Hands-on Deck. And the reason it works is that this isn't just a skill — this is PowerPoint. The actual application: PowerPoint, Google Slides, Keynote, whatever you use. This is that, but for an agent, presented as a CLI. Every gesture you make in a deck app maps to a command. Click a box and type, drag a shape from here to there, look at a slide – agent can do it all in a command. And that changes how the agent behaves. With this CLI it works and thinks like a designer — it looks, makes an edit, looks again, makes another surgical edit. Compare that to Anthropic's pptx skill, built on the idea that Claude is a great programmer: it literally writes code to manipulate the deck, hand-editing XML and hoping it doesn't break anything else in the middle. The real test isn't creating something once — it's whether it can make surgical edits like you want. That's what I did in this video walkthrough and my claude crushed it! Check it out for yourself. So decks can be built like a designer now — with real flavor and taste. If you spend hours every week on decks, this gives those hours back. You can install it as a skill in Claude Code, Codex, whatever you use. Works every harness that supports skills. Let me know if you make something cool with it.

I solved building decks with AI agents — by giving them a CLI tool like Powerpoint or Google Slides. AI could already make a beautiful deck if you asked it to using Ant's pptx skill. The problem was working with it. If it made one alignment mistake, fixing it on one slide would break something on another, and it became a game of whack-a-mole. One time I spent two days playing AI roulette, hoping the next prompt would finally fix the thing, and ended up building the whole deck by hand because I was on a deadline. So I built Hands-on Deck. And the reason it works is that this isn't just a skill — this is PowerPoint. The actual application: PowerPoint, Google Slides, Keynote, whatever you use. This is that, but for an agent, presented as a CLI. Every gesture you make in a deck app maps to a command. Click a box and type, drag a shape from here to there, look at a slide – agent can do it all in a command. And that changes how the agent behaves. With this CLI it works and thinks like a designer — it looks, makes an edit, looks again, makes another surgical edit. Compare that to Anthropic's pptx skill, built on the idea that Claude is a great programmer: it literally writes code to manipulate the deck, hand-editing XML and hoping it doesn't break anything else in the middle. The real test isn't creating something once — it's whether it can make surgical edits like you want. That's what I did in this video walkthrough and my claude crushed it! Check it out for yourself. So decks can be built like a designer now — with real flavor and taste. If you spend hours every week on decks, this gives those hours back. You can install it as a skill in Claude Code, Codex, whatever you use. Works every harness that supports skills. Let me know if you make something cool with it.

Nityesh

69,744 views • 1 month ago