BrowserSkill: Let AI Use Your Already-Logged-In Browser, Without Interrupting You

BrowserSkill is an innovative tool that enables artificial intelligence to utilize a pre-logged-in browser without disrupting the user's workflow. This is particularly useful for developers who have struggled with the challenges of browser automation, such as captchas, SMS codes, QR scans, device fingerprints, and risk controls, which often hinder automated processes.

The tool's unique approach involves borrowing the browser that is already logged in, rather than creating a new instance, which helps in maintaining trust and avoiding suspicious behavior.

BrowserSkill comprises two local components: a CLI/daemon and a browser extension. Once installed, users can command their existing automation agents (like Cursor, Claude Code, Codex, or WorkBuddy) to control their already-logged-in browser through the bsk command. This reuses real login states, leveraging a device's history and valid session, which significantly increases the likelihood of successful automation compared to freshly created environments.

A notable feature of BrowserSkill is its commitment to transparency and user control. The tool runs in a separate, visible Agent window, allowing users to monitor the agent's activities and ensuring that the automation process remains visible and understandable. It also includes a built-in human-in-the-loop system. When the agent encounters tasks such as captchas, logins, or confirmation dialogs, it halts and prompts the user to intervene.

After taking over, the agent resumes its task, demonstrating a balance between automation and human oversight.

The key distinction of BrowserSkill from traditional headless automation tools like Playwright or Puppeteer lies in the principle of borrowing trust instead of creating new instances. Headless browsers generate new fingerprints, cookies, and login states, which are typically suspicious and may trigger security measures. In contrast, BrowserSkill repurposes existing browser instances, using established fingerprints and session data that are already trusted by websites.

This shift from faking trust to borrowing trust represents a fundamental paradigm change in browser automation.

However, it is important to note that BrowserSkill requires users to manage their security conscientiously. As it uses the user's real, logged-in browser, there are inherent security considerations that need to be addressed. The tool is designed with caution, mandating that users explicitly borrow tabs, return them once the task is complete, and handle sensitive steps with care.

While BrowserSkill offers transparency and user control, it does not provide full autopilot mode, ensuring that users remain actively involved in the automation process.

For those interested in exploring BrowserSkill further, the project's README and core documentation are available in Chinese, providing localized support. Additionally, users are encouraged to express their appreciation by giving a star on the original repository, which helps in the ongoing maintenance and development of this innovative tool.