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Sustn, Turn unused Claude Code tokens into PRs that clean your codebase

Hacker News

Sustn, Turn unused Claude Code tokens into PRs that clean your codebase

Hi HN! I use Claude Code a lot, but my token usage is directly proportional to how long I'm willing to sit there prompting it. If I'm not at my desk thinking up tasks and feeding them in, the tokens just go unusued[which i weirdly feel bad about]. over the past couple of days, I hacked on sustn, a tool that scans your repo, figures out what needs fixing on its own (dead code, missing tests, security issues, etc.), and puts it in a prioritized list. Then it just starts working through the list - whether you're there or not. When it's done with a task, it either creates a PR automatically or waits for your approval - you choose. You can reorder the list to control what gets picked up next, set a schedule (e.g let it run overnight), set a token budget, and add your own tasks manually too. It runs on your local Claude Code instance, so nothing leaves your machine. Free and open source - https://github.com/Ghvstcode/sustn Still very early but would love feedback.

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, claude, tasks · Missing: agents, macos, agent
95%95% 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
61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: open source, 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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
23%23% 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
17%17% 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
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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