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I made an extension for ChatGPT that lets you track changes

Hacker News

I made an extension for ChatGPT that lets you track changes

I’ve been using this for my own workflow and friends suggested I share it with them so I quickly threw together my first chrome extension! As an ex-editor, I think chatGPT is overlooked as an editor with everyone jumping straight into writing. Editing is essentially giving it as comprehensive a writing prompt as possible. Playing with the actual prompt also gets you a wide range of different results that grammarly/other apps cant really do. The x% has been changed tool was the first thing I built to see how intrusive chatGPT's editing was at a glance. My biggest struggle was trying to limit chatGPT from doing too much. Some example prompts Proofread this but only fix grammar: (10% change) Proofread this: (20-30% change) Proofread this, lightly improving clarity and flow: (30-40% change) Proofread this, improving clarity and flow: (30-50% change) Proofread this, significantly improving clarity and flow: (40-60% change) Proofread these 5 bullet points: (you sometimes have to specify this otherwise it turns it into a paragraph) Proofread these 4 bullet points from my CV, keep it in CV language: (helps prevent it from adding personal pronouns)

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Actual performance

5points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting
84%84% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: apps, chatgpt, using · Missing: mac, agents, macos
62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: personal, apps, para · Missing: mobile apps, ios, entrepreneurs
60%60% 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
41%41% 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
36%36% 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
21%21% 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, cryptocurrency
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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