Claude-File-Recovery, recover files from your ~/.claude sessions

Hacker News

Claude Code deleted my research and plan markdown files and informed me: “I accidentally rm -rf'd real directories in my Obsidian vault through a symlink it didn't realize was there: I made a mistake. “ Unfortunately the backup of my documentation accidentally hadn’t run for a month. So I built claude-file-recovery, a CLI-tool and TUI that is able to extract your files from your ~/.claude session history and thankfully I was able to recover my files. It's able to extract any file that Claude Code ever read, edited or wrote. I hope you will never need it, but you can find it on my GitHub and pip. Note: It can recover an earlier version of a file at a certain point in time. pip install claude-file-recovery

Visit product View on Hacker NewsFeb 27, 2026

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

83%83% 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 · Missing: supports, reddit linkedin, podcasting

53%53% 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: ide, io · Missing: https docs, excited, just released

45%45% 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 · Missing: mobile apps, ios, personal

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

25%25% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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