
This is browser automation built specifically for AI agents to control through CLI commands. The workflow is clean: open a URL, snapshot to get element references like @e1 and @e2, then interact using those refs to click, fill forms, or extract data. It handles the stuff you'd expect like screenshots, PDF generation, and state persistence for login sessions, plus some nice touches like connecting to an existing Chrome instance or running tests on iOS Simulator. The ref-based interaction model is smart because it sidesteps the usual brittleness of CSS selectors. If you're building agents that need to interact with websites programmatically, this gives you the primitives without forcing you into a heavier framework.
$ npx -y skills add countbot-ai/countbot --skill agent-browser --agent claude-codeInstalls into .claude/skills of the current project.
Every browser automation follows this pattern:
agent-browser open <url>agent-browser snapshot -i (get element refs like @e1, @e2)agent-browser open https://example.com/form
agent-browser snapshot -i
# Output: @e1 [input type="email"], @e2 [input type="password"], @e3 [button] "Submit"
agent-browser fill @e1 "user@example.com"
agent-browser fill @e2 "password123"
agent-browser click @e3
agent-browser wait --load networkidle
agent-browser snapshot -i # Check result
# Navigation
agent-browser open <url> # Navigate (aliases: goto, navigate)
agent-browser close # Close browser
# Snapshot
agent-browser snapshot -i # Interactive elements with refs (recommended)
agent-browser snapshot -i -C # Include cursor-interactive elements (divs with onclick, cursor:pointer)
agent-browser snapshot -s "#selector" # Scope to CSS selector
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