BrowserAct Skills - Open-Source AI Agent Browser Automation CLI Tool

What is BrowserAct Skills

BrowserAct Skills is a browser automation CLI tool for AI Agents, solving the core pain points when Agents control browsers, such as no Cookie environment, anti-scraping blocking, CAPTCHA blocking, human-machine collaboration disconnect, etc. Through a three-layer progressive architecture, including environment layer → execution layer → human layer, the tool enables Agents to stably execute tasks in real browser environments.

Main Features of BrowserAct Skills

Anti-Detection Environment: Supports dual-mode control via command line and vision, bypassing anti-scraping mechanisms and avoiding being identified as a Bot.
Three-Layer Progressive Structure: The environment layer handles fingerprint spoofing, TLS rotation, and proxy switching; the execution layer automatically cracks CAPTCHAs and stealthily extracts protected pages; the human layer generates remote assistance links, and after the user takes over from any device and completes the task, the Agent seamlessly continues the task.
Three Browser Modes：chrome mode reuses local login state,stealth privacy mode is used for login-free batch scraping,stealth fixed identity mode is used for parallel multi-browser operation of logged-in accounts.
Multi-Account Isolation: Through Stealth Browser + Static Proxy, each account runs in an independent browser environment, bound to an independent login state and network environment.
Concurrent Zero Interference: When running in parallel across browsers, Cookies, fingerprints, and proxies are completely independent; when running multiple sessions in the same browser, the login state is shared but execution does not block each other.
Skill-Forge Extension: Automatically explores the target website's API and data paths, generates reusable Skill packages, and the Agent can subsequently directly reuse verified paths to execute batch tasks.

Technical Principles of BrowserAct Skills

Environment Layer Disguise: Through dynamic browser fingerprint spoofing, TLS fingerprint rotation, and residential proxy switching, each session presents real user network characteristics, evading anti-bot detection.
Execution Layer Penetration: Built-in automatic CAPTCHA parsing engine and stealthy data extraction channel, the Agent can directly scrape protected page content without manual intervention.
Human Layer Continuation: When a task encounters obstacles, a real-time remote collaboration link is generated. After the user intervenes and completes it, the system automatically restores the session context, achieving seamless human-machine relay.
Indexed Interaction: Maps page elements to compact numeric indexes. The Agent controls the browser through numbered instructions, without needing to parse the DOM or load the accessibility tree.
Semantic Memory: Binds a descriptive label to each browser session. The Agent automatically matches the most suitable browser environment to execute operations based on task semantics.

How to Use BrowserAct Skills

Environment Preparation: Ensure the system is Windows, macOS, or Linux, and an AI Agent that supports Shell commands has been installed.
One-Click Installation: Issue the "install browser-act" command to the Agent and provide the GitHub Skill source address. The Agent will automatically complete installation and verification.
Environment Detection: After installation is complete, the Agent will automatically obtain the environment status, browser list, and available commands at the start of each session.
Extract Page: Directly have the Agent execute the task of "extracting the content of a certain webpage," and BrowserAct will automatically scrape protected pages in zero-configuration mode.
Create a session: Tell the Agent to open a specific website and create a named session; all subsequent operations are executed independently within that session.
Check status: The Agent returns a list of indexed interactive elements on the current page, so the page structure can be understood without parsing the DOM.
Execute operations: The Agent precisely controls the browser through indexed instructions (such as clicking the 3rd element or entering text in the 2nd input field).
Mode selection: Based on task requirements, have the Agent switch among three browser modes—reuse the local Chrome login state, privacy-preserving batch scraping, or fixed-identity parallel multi-account operation.
Install extension: If you need to automatically generate a reusable Skill, have the Agent install the browser-act-skill-forge extension, after which you can directly describe the target website and data fields.
Human-agent relay: When encountering a CAPTCHA or QR code login, the Agent automatically generates a remote assistance link; after you complete the operation from any device, the Agent seamlessly continues the task.
Security confirmation: For sensitive operations such as browser creation and deletion, Profile import, and proxy changes, your explicit independent approval is required each time, and prior authorization is not automatically inherited.

Core advantages of BrowserAct Skills

Uninterrupted human-agent relay: The only built-in remote-assist remote collaboration link; when a CAPTCHA or QR code is encountered, a real-time link is generated, and after the user takes over the operation from any device and completes it, the Agent seamlessly continues the task without interruption or errors.
Three-layer progressive anti-detection: Environment layer + execution layer + human layer, covering the full spectrum from pure automation to required human intervention; most anti-scraping mechanisms are resolved before reaching the Agent.
Agent-native efficient interaction: Uses indexed instructionsclick 3 / input 2 "...", so the Agent does not need to parse the DOM or load the Accessibility Tree, and Token efficiency is significantly higher than natural language or JSON/HTML output solutions.
Self-accumulating and reusable Skills: Skill-Forge automatically explores the target website's API and data paths to generate a deployable Skill package; subsequent batch tasks directly reuse the verified paths for execution, without the Agent needing to re-understand the page structure each time.

Project address of BrowserAct Skills

GitHub repository：https://github.com/browser-act/skills

Comparison of BrowserAct Skills with similar competing products

Comparison dimension	BrowserAct Skills	browser-use
Positioning	Browser automation for AI Agents CLI + Skill infrastructure, emphasizing supplementing the "execution layer"	The most active community AI browser automation SDK framework(94k+ stars), emphasizing end-to-end Agent autonomous decision-making
Architecture form	CLI tool + Skill package (Agent invokes commands through Shell)	Python/TypeScript SDK + self-developed `bu-ultra` dedicated model (LLM-first)
Core interaction paradigm	Indexed instructions（`click 3` / `input 2 "..."`), the Agent does not need to parse the DOM, with extremely high Token efficiency	Natural language + DOM parsing, the Agent reads the accessibility tree or DOM and autonomously decides clicks and inputs
Anti-detection capability	Three progressive layers: environment layer (fingerprint/TLS/proxy rotation) → execution layer (automatic CAPTCHA solving/`stealth-extract`) → human layer (remote assistance)	Built-in stealth browser technology bypasses basic anti-scraping, butno system-level layered architecture, and advanced CAPTCHAs must be handled on its own
Human-machine collaboration link	✅ Built-in `remote-assist`: generates a real-time link, and after the user scans the code/verifies, the Agent seamlessly continues, without interrupting the task	❌ No built-in human-machine collaboration: when encountering CAPTCHAs, QR code scans, 2FA, etc., external interruption is required, and the Agent directly reports an error or stalls
Browser modes	Three modes：`chrome`(reuse local login state),`stealth` privacy (zero-residue batch scraping),`stealth` fixed identity (parallel multi-account)	Mainly provides stealth mode,no ability to reuse local Chrome login state, and each startup is mostly a blank environment

Application scenarios of BrowserAct Skills

Automated data collection: reuse existing login state to enter WeChat Official Account backend, Zhihu, Xiaohongshu, etc., extract article data and user information, without repeated QR code scans.
Bypassing anti-scraping mechanisms: normally scrape content on platforms with strict anti-scraping such as Xiaohongshu, and automatically handle dynamic pages.
Human-machine relay collaboration: when encountering CAPTCHAs or QR code login, generate a remote assistance link, and after the user completes the operation, the Agent automatically continues without interrupting the task flow.
Multi-account matrix operations: run e-commerce stores and social media multi-accounts independently, avoiding cross-environment contamination.
Batch skill accumulation: through Skill-Forge, solidify repetitive website operations into reusable Skills, and then directly execute them in batches.