Spectre – Cursor for Google Docs

Hacker News

Hi HN! I'm Seth from Spectre, the world's first Cursor for Google Docs. Everyone's building a Cursor for writing, but no one is integrating into existing platforms that have billions of monthly active users such as Google Docs and Microsoft Word. We currently have two features - an autocomplete that's similar to Cursor's 'tab' system and a diff editor activated with Ctrl + Shift + K over a selected piece of text. You can check out a demo on our website and download the extension from there. Not many people are building this deeply in extensions from what we have seen so we are super stoked to be leaders in this space. Our core belief is building delightful software that people enjoy; we would love to hear your feedback so we can make Spectre 10x better with each release! Also let us know what sites/apps we should integrate on next :)

Visit product View on Hacker NewsJun 24, 2025

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

95%95% 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: exist, existing, io · Missing: https docs, excited, just released

67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: apps, month, google · Missing: mobile apps, ios, personal

64%64% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform, users · Missing: plus, intuitive, reviews

32%32% 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

23%23% 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.

Incorrect prediction on native model

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