ATM, a tiny terminal task manager for local coding agents

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Hi HN, I made ATM, short for Agent Task Manager. It is a small CLI/TUI that shows which local coding agents are running on your machine, which repo they are in, and whether they look active, idle, stale, or just present as a process. It currently recognizes common agent CLI processes like Codex, Claude, Gemini, Aider, OpenCode, Goose, Amp, and Cursor Agent. Codex has the deepest support right now: ATM can read local session metadata to show the project, session path, last activity, and a compact "what just happened" summary. I built it because I kept ending up with several agents running across different repos and wanted something friendlier than ps for answering: "what is still alive, where is it working, and has it gone quiet?" Install: curl -fsSL https://github.com/artpar/atm/releases/latest/download/insta... | sh Repo: https://github.com/artpar/atm It is early, tiny, and CLI-first. I’d love feedback from people running multiple local agents at once because right now its a very basic.

Visit product View on Hacker NewsMay 21, 2026

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

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.

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

71%71% 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

36%36% predicted probability of success on TrustMRR, 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

36%36% 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

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

21%21% 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

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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