agentwatch

React DevTools, for browser AI agents. Drop a translucent overlay onto every tab that shows what your agent is trying to do, what it just clicked, and what it's about to do next.

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Why

Browser-use, Playwright agents, computer-use models — they're all black boxes to the developer watching them. The agent moves the mouse, types into a field, the page reloads, then it errors out, and you're left guessing what it thought it was doing.

agentwatch adds a tiny floating overlay to every tab. Your agent code pushes one-line status updates ("goal: book a flight", "last action: clicked search", "next action: type SFO"), and the overlay shows them live, framework-agnostic.

The result: bug screenshots that are self-explanatory. Demo GIFs that viewers actually understand. Pair-debugging sessions where the human can intervene the moment the agent goes off-rails.

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Architecture

┌──────────────────────────┐        ws://127.0.0.1:8765        ┌──────────────────────────┐
│  Your agent (any lang)   │ ──────────────────────────────▶   │  Chrome MV3 extension    │
│  agentwatch.announce(    │      broadcasts status JSON       │  injects floating overlay│
│      goal=..., last=...) │                                   │  on every tab            │
└──────────────────────────┘                                   └──────────────────────────┘

The SDK runs a localhost WebSocket broadcaster in a background thread. The extension's content script connects to it on every page load. Each announce() call updates the overlay in place with a green flash.

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Install (2 steps)

1. Install the Chrome extension

git clone https://github.com/yubinkim444/agentwatch.git
cd agentwatch

In Chrome / Edge / Brave:

• Open chrome://extensions
• Toggle Developer mode (top-right)
• Click Load unpacked
• Select the extension/ folder

A small overlay appears in the bottom-right of every tab, showing a disconnected (yellow) dot until your agent connects.

2. Install the SDK

pip install agentwatcher

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Use it

Python

from agentwatch import AgentWatch

with AgentWatch() as aw:
    aw.announce(goal="Book a one-way flight SFO → JFK for tomorrow")

    # ...do agent stuff...

    aw.announce(step=1, last_action="Opened google.com/flights",
                next_action="Click the origin field")
    # ...
    aw.announce(step=2, last_action="Typed 'SFO'",
                next_action="Click the destination field")

Or imperatively, without the context manager:

import agentwatch
agentwatch.start()
agentwatch.announce(goal="...", last_action="...", next_action="...")

Any other language

Open a WebSocket to ws://127.0.0.1:8765 and send JSON like:

{"goal": "Book a flight", "last_action": "Clicked search", "next_action": "Type SFO"}

Every connected tab's overlay updates immediately.

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Recognized fields

Field	What the overlay shows
goal	Top-line objective.
last_action	What the agent just did.
next_action	What the agent is about to do.
step	Optional step counter / index.
error	Highlighted in red. The error row only appears when set.

Any other keys are kept in the broadcast payload but not rendered by the default overlay — fork the extension if you want to add custom rows.

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Pairs nicely with

• playwright, selenium, browser-use, any computer-use agent.
• A screen-recorder. The overlay + your tool together produce demo GIFs that explain themselves.

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Companion projects

• mcp-rec — VCR for MCP servers.
• llm-cache-proxy — disk cache for OpenAI/Anthropic API calls.
• promptlock — lockfile for prompts.
• context-diff — git diff for Claude Code context windows.

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License

MIT © yubinkim444