A local-first browser
memory-management agent
Tab Agent groups tabs, autonomously manages low-need tabs, wakes related contexts, learns from feedback, and optionally adds OpenAI-powered summaries and recommendations. The core agent runs locally in Chrome.
Why this exists
Browser memory management is still mostly generic and rule-based. It does not know which tab you will need in five minutes, which group belongs to your current task, or which tabs you repeatedly regret losing.
Tab Agent starts with the browser because it is a visible, measurable wedge into a larger idea: personalized memory management that saves resources without interrupting real work.
What the current product does
On-device grouping
Gemini Nano groups your tabs by topic locally in Chrome, creating a usable context map before any autonomous action happens.
Autonomous sleep
A conservative local policy sleeps low-need tabs based on recency, behavior history, and protection rules.
Context wake
When you return to a working context, the agent can wake related slept tabs so the relevant cluster is ready again.
Feedback loop
Undo, Protect, Good, and Bad feedback give the agent signals about which autonomous decisions helped and which were mistakes.
Action log
The Stats page shows what the agent did, why it acted, and what happened after so the system stays explainable.
Optional OpenAI layer
OpenAI is advisory only. It can add policy summaries and recommendations, but the real-time browser agent still runs locally.
How the agent works
Local core vs optional cloud layer
The core agent works without OpenAI. Local features include grouping, autonomous sleep, context wake, local behavior memory, and the full feedback loop.
The optional backend layer adds study submission, admin review, and OpenAI-assisted policy summaries. OpenAI is advisory only and does not control real-time browser actions.
You can inspect the live telemetry and training-style graphs on /admin.
How to install
The live site is the product page and backend surface. The real product is the Chrome extension, which you currently install in developer mode from GitHub.
Enable Gemini Nano
Open Chrome and set these flags, then relaunch:
chrome://flags/#prompt-api-for-gemini-nano -> Enabled chrome://flags/#optimization-guide-on-device-model -> Enabled BypassPerfRequirement
Then open DevTools and run:
await LanguageModel.create()
This downloads the local model. When it finishes, verify with await LanguageModel.availability() and confirm it returns "available".
Download the extension
Clone or download the extension repo from github.com/MaykaS/tab_agent
git clone https://github.com/MaykaS/tab_agent.git
Load in Chrome
Go to chrome://extensions, enable Developer mode, click Load unpacked, and select the tab agent folder.
After install, check the popup for grouping, open the Stats page, watch autonomous activity, and optionally generate an AI summary if the backend OpenAI layer is enabled.
Research and product direction
Tab Agent began as a manual AI-assisted tab organizer and has now evolved into a working agentic browser prototype. It is being used to test how autonomous tab memory management compares with both static rules and manual assistant workflows.
More details on evaluation framing and comparison baselines live on /evals.