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Browse.sh - Give your agents muscle memory for automating the web

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browse.sh — an open catalog of browser automation skills for any website. Find reusable SKILL.md recipes that teach AI agents to complete tasks online, and install them with the browse CLI.

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Maker
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Hey Product Hunt 👋


I'm Shrey,

Over the last year, we've watched AI agents get remarkably good at using browsers. But we've also noticed something strange: every time an agent visits a website, it starts from zero.

It re-explores the interface, re-discovers buttons, re-learns navigation paths, and re-finds the same workflows it already completed yesterday.

Humans don't work that way.

Once you learn how to search Zillow listings, review a GitHub PR, or book a campsite on , you don't relearn the entire website every time you come back.

Agents shouldn't have to either.

That's why we built , an open catalog of browser skills that agents can install and reuse across the web. Instead of exploring a website from scratch, agents load the relevant skill and execute against a known workflow.

The result is faster execution, lower token costs, more reliable outcomes, and better multi-site workflows. Today, the catalog includes 250+ skills across real websites and applications, including partner skills like submitting reimbursements on Ramp, creating projects on Lovable, extracting document data on Reducto, and many more.

And when a skill doesn't exist yet, can create one.

Behind the scenes, is powered by Autobrowse, our system that runs tasks in real browsers, analyzes traces, DOM changes, network activity, screenshots, and failures, then continuously improves the workflow until it converges on a durable strategy.

Over time, one successful browser run becomes a reusable skill that anyone can install.

is open source, free to use, and available today.

We'd love your feedback:

- Which websites do your agents struggle with most today?
- What skills should we add next?
- What workflows are you automating with AI agents?

We'll be around all day answering questions. Thanks for checking us out 🤞

 This is honestly one of the more interesting takes on browser agents I’ve seen lately.

The idea that agents repeatedly “forget” workflows every session feels so obvious once you say it out loud. Humans build muscle memory for interfaces naturally, but most agents today basically wake up with browser amnesia every morning !

A few things I’m really curious about:

  1. How durable are these skills when websites change their UI or workflows slightly? Is Autobrowse optimizing more around visual understanding, DOM structure, behavioral patterns, or a mix of all three?

  2. How do you think about “skill drift” over time? For example, if an agent learns a workflow extremely efficiently, is there a risk it becomes too rigid and fragile when a site evolves?

  3. The open catalog direction is super interesting too. Do you see eventually becoming something like an “npm for browser skills,” where agents dynamically install and compose workflows across the web?

And honestly, one of the most exciting parts for me is the multi-site workflow angle. It feels like that is where agents start becoming genuinely useful.

Really cool work. Excited to see where this goes.

Maker

 thanks for the kind words! to answer your questions:

  1. skills mainly describe how to accomplish a task on the current site based on the DOM structure & any internal APIs / network requests it can discover, so there's a possibility that the optimal approach goes stale or changes over time. However, each skill usually details multiple approaches & fallbacks to avoid this issue.

  2. Skill drift is definitely a possibility, but the benefits of operating at the agent instruction level in markdown is that agents can quickly steer to different approaches, unlike scripting which either opaquely succeeds or fails. We also routinely test any skills submitted to to ensure that they're up to date and still detail the optimal approach!

  3. Definitely! Thanks to the community contributing new skills, it's super easy to create "skill bundles" which compose functionality from individual sites together. You can try this yourself by telling your agent to use `browse skills find [query]` repeatedly when creating a skill bundle. In our video above, you can see us doing this to plan out a camping trip and generating a new skill bundle, `/hiking-trip-book`. The possibilities are endless!

 this is a context window + missing memory saving loop issue, easy fix

 Will skills have versioning, ratings, verified maintainers, or test-run results so users know which workflows are reliable before installing them?

 The problem you're solving — agents relearning the same workflows from scratch — maps directly onto a monitoring gap that founders often hit once their product launches: knowing in real time when developers, investors, or potential partners are discussing across Reddit threads, YouTube tutorials, or niche dev forums. MentionFox's lead-detection engine surfaces text and audio mentions of your product from sources most tools miss, so you can catch integration requests or competitor comparisons the moment they appear, not days later. Check it out at — in 30 seconds you can set up a alert and start turning organic conversations into qualified pipeline.

Maker

Hello hunters! We're so excited to be back and launching browse.sh. I'm Paul, founder of Browserbase. If you have any questions, I'd be happy to help answer them.

Congrats the on the launch! We've been using Browserbase to benchmark and prototyping how to enforce/apply the content at the harness layer instead of context layer! Love it!

Maker

  skills in the harness will definitely give your agents the edge they need, enforcing the workflow rather than just hoping that the agent picks it up.

Maker

The web was built for humans, and we are happy to launch this skills catalog that finally makes the web a playground for your Claude Code! You're building a web app that needs data that doesn't exist on an API, or you're just looking to automate your weekly lunch planning? is for you!

If a team is choosing between (a) writing Playwright scripts, (b) using a generic LLM browser loop, and (c) installing a Browse.sh skill, what’s the switching trigger where (c) becomes the clear winner—and what types of workflows should *not* be turned into skills yet?
Maker

Hey !

The trigger where using a skill is the clear winner for an automation is if you want the fastest/simplest path to automation. You can give OpenClaw/other agents access to and they'll be able to run every skill/automation on the platform.

Writing Playwright scripts is completely deterministic, but takes maintenance and time to create. Generic full agent loops are usually too loosely defined and won't stay within the bounds of the task. (skills here help you save tokens as well)

Things that should NOT yet be turned into skills are workflows that need 100% determinism. We're converging to agents becoming more reliable, but there's always a chance that it goes off course.

Looks nicely done, looking forward to try it !

Maker

 appreciate your support! What is one of the skills that you'd want to try out in your daily workflow?

This looks very interesting, definitely going to try a few of these skills this week.

Maker

 Thank you for the support! 🙌

this is very smart. i worked at Strawberry Browser before and this was a thing i thought about a lot

curious how you handle quality for open skills? like preventing stale, brittle, or low-quality workflows from spreading through the catalog

Maker

 We hand review all skills and requests to make sure that we're not getting straight slop into the official list.

Maker

 right now all skill runs are vetted by hand for success. We also routinely re-run skills every week to ensure quality. In the future as skill generation scales up, we may implement a consensus mechanism between different skill submissions to ensure most up-to-date info!

nice! I have been perplexed as to why the Claude browser plug-in doesn't already have this feature. I have wasted so much time re-reaching Claude the same steps over and over again because of this exact problem. Look forward to trying this out.

Maker

 100%, we’ve felt Claude in Chrome is a half-baked implementation at agentic browser capabilities. We built our CLI to fill those gaps!

There’s some level of stochasticity in the “perfect recipe” and resulting output for a given task. If multiple users each have a distinct generated skill to perform the same task uploaded to Browse.sh, how does the platform resolve these redundancies?

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