Cu

Cursor for Userscripts

Hacker News

Cursor for Userscripts

I’ve been experimenting with embedding an Claude Code/Cursor-style coding agent directly into the browser. At a high level, the agent generates and maintains userscripts and CSS that are re-applied on page load. Rather than just editing DOM via JS in console the agent is treating the page, and the DOM as a file. The models are often trained in RL sandboxes with full access to the filesystem and bash, so they are really good at using it. So to make the agent behave well, I've simulated this environment. The whole state of a page and scripts is implemented as a virtual filesystem hacked on top of browser.local storage. URL is mapped to directories, and the agent starts inside this directory. It has the tools to read/edit files, grep around and a fake bash command that is just used for running scripts and executing JS code. I've tested only with Opus 4.5 so far, and it works pretty reliably. The state of the file system can be synced to the real filesystem, although because Firefox doesn't support Filesystem API, you need to manually import the fs contents first. This agent is really useful for extracting things to CSV, but it's also can be used for fun. Demo: https://x.com/ichebykin/status/2015686974439608607

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Actual performance

56points
15comments
Made the leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, cursor, claude · Missing: mac, agents, macos
94%94% 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: filesystem, ide · Missing: https docs, excited, just released
68%68% 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, podcasting
64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal
30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% 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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