Gemini 2.5 Computer Use browser automation with Playwright-based agent loops and safety confirmations.
Works with
Implements a screenshot-to-action cycle: capture screen, send to Gemini, parse function calls, execute in Playwright, return results until task completion or turn limit
Supports multiple browser options: bundled Chromium (default), Chrome/Edge channels via COMPUTER_USE_BROWSER_CHANNEL , or custom executables like Brave
Includes safety confirmation workflow that prompts users before
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiongemini-computer-useExecute the skills CLI command in your project's root directory to begin installation:
Fetches gemini-computer-use from am-will/codex-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate gemini-computer-use. Access via /gemini-computer-use in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Source the env file and set your API key:
cp env.example env.sh
$EDITOR env.sh
source env.sh
Create a virtual environment and install dependencies:
python -m venv .venv
source .venv/bin/activate
pip install google-genai playwright
playwright install chromium
Run the agent script with a prompt:
python scripts/computer_use_agent.py \
--prompt "Find the latest blog post title on example.com" \
--start-url "https://example.com" \
--turn-limit 6
COMPUTER_USE_BROWSER_CHANNEL.COMPUTER_USE_BROWSER_EXECUTABLE.If both are set, COMPUTER_USE_BROWSER_EXECUTABLE takes precedence.
function_call actions in the response.safety_decision is require_confirmation, prompt the user before executing.function_response objects containing the latest URL + screenshot.--exclude to block risky actions you do not want the model to take.scripts/computer_use_agent.pyreferences/google-computer-use.mdenv.exampleMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
gemini-computer-use reduced setup friction for our internal harness; good balance of opinion and flexibility.
gemini-computer-use has been reliable in day-to-day use. Documentation quality is above average for community skills.
I recommend gemini-computer-use for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
gemini-computer-use fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Useful defaults in gemini-computer-use — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added gemini-computer-use from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
gemini-computer-use has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: gemini-computer-use is focused, and the summary matches what you get after install.
gemini-computer-use is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: gemini-computer-use is the kind of skill you can hand to a new teammate without a long onboarding doc.
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