AI agents that browse the web have a dirty secret: they're flying blind. They land on a page with no idea what's on the next one, what flows exist, or which buttons actually do something important. The result is a lot of wasted tokens, wrong clicks, and failed tasks. Hyperbrowser just shipped a practical fix for this: a Claude Code skill called /web that crawls any website and produces a web.md file -- a structured, LLM-friendly map of every page, action, flow, and interactive element on the site.
The idea is simple but the impact is real. Instead of sending your agent into a website cold, you run /web first. It hands the agent a complete map before it takes a single step.
The blind navigation problem
When you build an agent that needs to interact with a web app -- say, to fill out a form, trigger a workflow, or extract data from a dashboard -- the agent has to figure out the site's structure on the fly. It scrapes one page, guesses what to click next, and often ends up in a dead end or loops back to somewhere it's already been. This isn't a model intelligence problem; it's a context problem. The agent simply doesn't know the map.
Hyperbrowser specifically targets AI agent applications, optimizing infrastructure for autonomous browser agents with features like CAPTCHA bypass, session management, and AI agent optimization.
The /web skill is the latest layer on top of that infrastructure -- a pre-flight reconnaissance tool for agents.
How it works
The /web skill is a Claude Code skill -- a markdown file dropped into
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