Baton – A daemon that sends Claude to fix your GitHub issues

Hacker News

I got tired of the context-switching loop: pick an issue, read the context, write the code, open a PR, pick the next one. So I built Baton — a Python daemon that polls your GitHub issue tracker and dispatches Claude Code agents to work on them autonomously. How it works: - Polls `gh issue list` every 30 seconds for new issues - Claims an issue, spins up a git worktree (instant, shares the object database — no full clones) - Launches a Claude Code agent into that isolated workspace - When the agent opens a PR, Baton releases the slot and picks up the next issue - If one agent trashes its branch, the others don't care Everything is configured in a single WORKFLOW.md file — YAML config + Jinja2 prompt template. It reloads on each poll cycle so you can tune it without restarting.

Visit product View on Hacker NewsMar 29, 2026

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

97%97% 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.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

43%43% 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

32%32% 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.

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

22%22% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

18%18% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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