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It is becoming f*cking dangerous: one command in Claude Code turns your codebase into a map, 141K stars in 7 months 1. Install with uv, the package has two y's: uv tool install --python 3.13 graphifyy 2. Add the skill to Claude Code: graphify install 3. List tests, docs and images in .graphifyignore: test factories took 6 of the top 10 spots in a repo Graphify reviewed, each image gets its own subagent 4. In a repo you trust, start Claude Code at the root, type /graphify . (tree-sitter parses code with no LLM, Claude still spends tokens running it) 5. Open graphify-out/graph.html and read GRAPH_REPORT.md: most connected nodes first, then surprising connections 6. Ask with words from your code: graphify query "auth token", or trace a path: graphify path "A" "B" --undirected 7. Remind Claude to check the graph: graphify claude install, rebuild the code part on every commit: graphify hook install Every edge is tagged EXTRACTED, INFERRED or AMBIGUOUS: check the source before you trust the last two Official repo: github.com/Graphify-Labs/gra… Full guide in the article below

It is hard to believe, but 66,000 GitHub stars went to a way of running Claude Code without paying Anthropic 1. Open github.com/Alishahryar1/free…, on Mac or Linux run the curl installer from the README 2. Run fcc-server on Linux or open the Free Claude Code app on Mac and Windows, it opens the Admin UI 3. Turn on Proxy Authentication with your own token, by default the proxy is open to your whole network 4. Create an API key at build.nvidia.com, paste it under Providers, NVIDIA NIM, Add key, Save, then click Apply 5. Start the agent with fcc-claude 6. Switch in the native /model picker among providers you set up, 61 in the catalog, free and paid, DeepSeek, Kimi, Groq, Ollama 7. Add Fallback Models so a dead provider rolls to the next one, a failed request can consume usage from more than one Free routes mean other models, not Claude, Anthropic does not support this, and your code goes to the provider unless it is local The README claims 1.3B+ free tokens a month, availability and limits are set by each provider and can change Full guide in the article below

Whoever built this will put video editors out of work: raw footage in a folder, Claude Code hands back final.mp4 1. Paste the setup prompt from github.com/browser-use/video… into Claude Code, it installs itself 2. Export your ElevenLabs key first, the tool is free and open source, you pay for transcription and Claude usage 3. Drop your raw takes into one folder, cd there and run claude, transcription starts right away so test on one short clip 4. Type: edit these into a launch video 5. Read the plan it proposes and say OK, it does not touch the cut before that 6. Wait while it removes umms and dead space, ask for color grade, subtitles and overlays too, each overlay gets its own subagent 7. Approve the preview to get edit/final.mp4, every cut is checked first, up to 3 fix passes 30K+ GitHub stars, MIT license, works for talking heads, montages, tutorials, travel, interviews Claude reads a ~12KB transcript plus PNG filmstrips, frame by frame would be about 45M tokens Full guide in the article below

I still don't get why anyone builds a second brain for Claude Code from scratch when these 7 repos have over 75,000 stars combined 1. Teach Claude Obsidian's formats and tools with 6 skills from its CEO: github.com/kepano/obsidian-s… 2. Run wiki-ingest on text in inbox/, review the plan, get linked notes: github.com/AgriciDaniel/clau… 3. Save decisions and tasks with obsidian-save, load your current state next session with obsidian-world: github.com/eugeniughelbur/ob… 4. Run an unofficial Karpathy-style wiki with ingest, query and lint: github.com/Astro-Han/karpath… 5. Copy a starter vault plus 18 skills and 72 commands: github.com/undefined-ui/seco… 6. Turn your ChatGPT and Claude exports into linked notes, run only step 1 of its README: github.com/charlie947/ai-sec… 7. Split auto-loaded memory from wiki pages read on demand, ignore its tip to keep secrets in memory: github.com/MehmetGoekce/llm-… Pick one, they overlap: all seven work with plain Markdown you can open in any editor Full guide in the article below

It is becoming f*cking dangerous: one line in Claude Code builds a turbofan with 3,597 parts you can cut open and break 1. Install the open source skill (Node 22.20+): npx skills add AirsupHQ/machine-skill -g -a claude-code 2. Add Playwright in its folder: cd ~/.claude/skills/machine && npm i && npx playwright install chromium 3. Open a new Claude Code session in an empty folder and type: /machine a turbofan jet engine, the kind that pushes a widebody off the runway 4. Let Claude write down real dimensions, parts list and physics, then build it 5. Open the HTML file, drag the throttle, try explode, cutaway, x-ray 6. Hit the break button: it throws a fan blade and the solver computes the load the case has to hold 7. Film it from that folder with your file's name (needs ffmpeg): node ~/.claude/skills/machine/scripts/record.mjs turbofan.html out/turbofan.mp4 The makers' estimate: about an hour per machine You get one HTML file: the makers' demo counts 3,597 parts, nearly all blades, yours will differ, and the physics is a small model, not CFD Full guide in the article below

It is becoming f*cking dangerous: Claude Code turns into a web crawler for almost any website, and you write zero lines of code 1. Install Microsoft's Playwright CLI (needs Node.js 20+): npm install -g @playwright/cli@latest 2. Run playwright-cli install --skills in your project folder, it adds a browser skill to .claude/skills 3. Open Claude Code in that folder, paste the start URLs and add: use playwright-cli 4. Name the fields you need: titles, prices, links, dates 5. Tell it to follow internal links, skip duplicates and respect robots.txt 6. Open a second terminal tab and run playwright-cli show to watch the browser live 7. Ask Claude to save the results to data.json, then turn the run into a script and test it once so you can rerun it Even Microsoft's Playwright MCP README says coding agents increasingly favor CLI with skills over MCP because it is more token-efficient Full guide in the article below

This is getting out of hand: Karpathy shared one text file, and Claude Code turns your PDFs into a wiki it maintains for you 1. Make a folder and open Claude Code inside it 2. Create raw/ for your sources and wiki/ for the pages 3. Paste Karpathy's LLM Wiki idea file and ask Claude to write CLAUDE.md for your topic 4. Put a PDF, transcript or article in raw/ 5. Tell Claude to ingest it: a summary page, index.md and related pages updated, a new entry in log.md 6. Ask anything: it answers from wiki/ with citations, good answers can be saved as new pages 7. Ask for a lint pass now and then: contradictions, stale claims, orphan pages One source might touch 10-15 pages, so your knowledge is compiled once and kept current, not re-derived on every question Full guide in the article below

You are making a painful mistake if you still use Claude Code's default answers: one Markdown file rewrites how it talks to you 1. Type /output-style to see the four built-in styles besides Default 2. Run /output-style concise: every answer leads with the result, no preamble 3. Switch to explanatory: short ★ Insight blocks show why Claude wrote that code 4. Pick learning: Claude leaves TODO(human) spots for you to write yourself 5. Create your own: save diagrams-first.md in ~/.claude/output-styles with your rules 6. Add keep-coding-instructions: true so Claude still codes the same way 7. Restart Claude Code, run /output-style diagrams-first and ask it to explain your app It sets Claude's role, tone and format for every response in the session, so you stop repeating the same request in each prompt Full guide in the article below