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ask, a single open source binary for ChatGPT prompting and splicing
Hacker Newsask, a single open source binary for ChatGPT prompting and splicing
Hey everyone, Like most devs, I spend a lot of time in my IDE and switching to chatgpt in the browser is pretty annoying, so I built a simple CLI tool to talk in the terminal. One cool feature is the ability to write prompts in text files and then inject text from other files into that prompt. Makes it super easy to pass source files and other docs to chatgpt without leaving the IDE.
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Product HuntOn track for Day 1 leaderboard · Strong signals: chatgpt, single, open · Missing: mac, agents, macos97%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.
Hacker NewsStrong engagement from HN community · Strong signals: open source, ide · Missing: https docs, excited, just released61%61% 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 HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting59%59% 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, personal47%47% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive39%39% 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, revenue18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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