3.1k Downloads
Overview
Provide a ready-to-run Gemini 2.5 Computer Use agent loop using Playwright to control a real browser (Chromium/Chrome/Edge/custom) based on natural-language prompts, including screenshot-based perception, function_call actions, and safety-confirmed UI operations.
Key Advantages
1.Implements the full Gemini Computer Use browser-control loop (screenshot → model function_call → Playwright action → function_response) with minimal glue code needed from the user.
2.Straightforward CLI entry point (`computer_use_agent.py`) so you can start automating real websites from a single prompt and start URL.
3.Supports flexible browser backends via environment variables (bundled Chromium by default; Chrome/Edge channels or custom Chromium-based executables like Brave).
4.Built-in safety mechanisms like `require_confirmation` handling and an `--exclude` flag to block specific risky actions, plus guidance to run in sandboxed profiles/containers.
5.Uses Playwright for robust cross-platform browser automation, benefiting from its mature selector engine and device/viewport control (e.g., recommended 1440x900 viewport).
Use Cases
- Automating repetitive web UI workflows (filling forms, clicking through dashboards, downloading reports) driven by natural-language prompts instead of hard-coded scripts.
- Assisted web research tasks such as navigating a site, finding the latest blog post, and summarizing or extracting specific information from pages.
- Prototyping and evaluating Gemini 2.5 Computer Use capabilities against real-world sites with a controllable, inspectable agent loop.
- Creating semi-automated internal tools that let a human approve or deny high-risk browser actions via the `require_confirmation` mechanism.
- Running small-scale, supervised web regression checks or smoke tests where an agent navigates to key pages and verifies content visually.
Evaluation Scores
7.6
/ 10
Reliability
6.8
Functionality
8.2
Usability
7.5
Safety
8.0
Performance
7.2
Compatibility
7.8
Based on 1 evaluation · Latest: 3/19/2026
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Evaluation History (1)
7.6/103/19/2026▼
OS: linux-x64LLM: z-ai/glm-4.5-air
**Quick judgment**: This skill is a solid, developer-oriented wrapper for running Gemini 2.5 Computer Use browser agents via Playwright. It’s well-suited for experimental and small- to medium-scale web automation where you want a full screenshot→action loop and some built-in safety controls. It is not a turnkey, production-grade automation framework, but a pragmatic starting point you can extend.
**What it does well**
- Quickly wires up Gemini Computer Use with Playwright, including the core agent loop (screenshot, function_call parsing, action execution, function_response).
- Offers flexible browser selection (bundled Chromium, Chrome/Edge channels, or custom Chromium-based browsers like Brave) via environment variables.
- Provides safety-conscious features: `require_confirmation` prompts for risky actions, an `--exclude` mechanism to block operations you don’t trust, and guidance to run in sandboxed environments.
- Simple CLI workflow (set env vars, create venv, install deps, run with `--prompt`, `--start-url`, `--turn-limit`).
**Key risks and limitations**
- **Destructive browser actions**: Without careful use of `--exclude`, sandboxing, and confirmation prompts, the agent could perform harmful actions in live accounts (e.g., deleting data, changing settings, or initiating unwanted purchases).
- **Model and API dependence**: Relies on the Gemini 2.5 Computer Use model via `google-genai`; reliability and latency are constrained by external API availability, quotas, and costs.
- **Automation brittleness**: As with any UI-driven automation, DOM/layout changes, popups, or unexpected modals can cause failures; there’s no explicit mention of robust error-handling, retries, or observability.
- **Developer-focused**: Setup (Python venv, Playwright install, env scripting) presumes some developer experience; there’s no GUI or orchestration layer.
**Best-fit scenarios (recommended use)**
- You want to **experiment with Gemini Computer Use** on real websites using a reproducible, inspectable Python/Playwright setup.
- You need an **agent loop with safety confirmation** for risky UI actions, and you’re comfortable supervising the agent’s behavior.
- You’re building **internal tools or prototypes** that automate browser workflows for your own team, where occasional flakiness is acceptable.
- You plan to **extend or integrate** this agent loop into a larger system (e.g., adding logging, guardrails, or orchestration) rather than use it as a final, production-ready solution.
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