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OmniGet is a surprisingly useful open-source desktop downloader for far more than YouTube

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#OmniGet#Open Source#Downloader#Desktop App#yt-dlp#Developer Tools
OmniGet is an open-source desktop downloader that goes beyond YouTube and supports many common media sources. It is useful for users who want a practical local tool instead of relying on browser extensions or single-site downloaders. OmniGet is one of those tools that looks like a simple downloader at first — then turns out to be much broader. What makes it worth a look native desktop app for Windows, macOS, and Linux no ads, no account, no telemetry claims on the official site downloads from YouTube, TikTok, Reddit, X, Vimeo, Bilibili and more can also pull full online courses from platforms like Udemy and Hotmart bundles yt-dlp and FFmpeg so the setup is lighter than many DIY stacks What other sources reveal The GitHub repo and official site both point to a bigger pitch than the viral one: built-in previews and quality selection global hotkey workflow plugin ecosystem document/course reading and study features torrent and peer-to-peer transfer support
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Graphify turns any folder into a queryable knowledge graph for AI coding agents

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#Graphify#Claude Code#Knowledge Graph#AI Agents#Developer Tools#Open Source
Graphify turns a folder into a queryable knowledge graph so AI coding agents can navigate project context more deliberately. It helps with codebase understanding, dependency discovery, and more grounded agent responses. Graphify is a sharp idea for agent-heavy workflows: point it at a folder and turn code, docs, PDFs, markdown, and images into a navigable knowledge graph instead of forcing the model to reread raw files every time. What you get interactive knowledge graph Obsidian-ready vault wiki-style markdown map plain-English Q&A over the project Why people care The project claims up to 71.5x fewer tokens per query versus reading raw files directly, which is exactly why it caught attention so quickly in the Claude Code crowd. Fast start Good questions to ask What calls this function? What connects these two concepts? What are the most important nodes in this project?
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