Tidbits – Quick save any text without switching windows

Hacker News

This is my super narrow, streamlined take on Raycast x Obsidian x Notes. - Select text in any app - Press ⌘⇧. - A floating panel appears over your current window. Pick a page (or create one), hit Save. The whole thing takes under 2 seconds to dump and organize text into local files. I journal, read, and research with LLMs all on my laptop. Between all of that, I'm always copy-pasting text into some new "simple" knowledge base that is just too bloated for what I need (Notion, Obsidian, Craft, etc). I honestly just prefer Google Docs but hate copy-pasting. So I made Tidbits to quick save text easily and have started hoarding all the interesting tidbits I want to keep for later. I've been using it for a few months: How I use it -- pages have a "Copy path" button, and so does the master folder. I'll use those paths with Claude Code when planning or journaling as a more explicit and intentional memory/context control. I really hate how ChatGPT will remember arbitrarily details like what I cooked for dinner but have no recollection of my ongoing physical injury. Or sometimes ChatGPT will just bring up irrelevant context to something I'm discussing with it. Open-sourced because I want transparency in anything that asks for permission. Plus would love to get feature requests and expand this!

Visit product View on Hacker NewsMar 30, 2026

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2points

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Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, google, new · Missing: mac, agents, macos

98%98% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting

82%82% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: month, google, way · Missing: mobile apps, ios, personal

39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: plus · Missing: platform, intuitive, reviews

29%29% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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