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Steam Game Idler – Open-Source Steam Automation Tool (Tauri and Rust)

Hacker News

Steam Game Idler – Open-Source Steam Automation Tool (Tauri and Rust)

If you're a PC gamer, you know Steam's trading card system is tedious. You need to idle games for hours to get card drops. For 500+ game libraries, that's impractical. Existing solutions like ArchiSteamFarm are powerful but complex (JSON configs, CLI-heavy, designed for headless servers). Idle Master was great but abandoned in 2016 and Idle Master Extended has its bugs too. Happy to answer questions about the tech stack, Steam APIs, or anything else. Also open to feedback and feature requests. Note: This is a personal project I use myself. Steam's ToS is vague on automation, so use at your own risk. No bans reported in 10+ years of similar tools existing, but YMMV.

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRFits verified-revenue profile · Strong signals: personal, trading · Missing: mobile apps, ios, entrepreneurs
51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: apis, open · Missing: mac, agents, macos
49%49% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, io · Missing: https docs, excited, just released
38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
9%9% 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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