mcpField
F
first-run

first-run

github.com/anthropicsAgent workflows19.0k82 installsUpdated 5d ago
Repository

About first-run

first-run is a guided onboarding skill for users running the computer_use demo for the first time. It checks setup without exposing the API key, runs a browser-only task, and guides users through viewing its trajectory.

Key features

  1. 01Check environment and dependencies
  2. 02Verify API key presence without displaying it
  3. 03Run a headless browser task
  4. 04Explain streamed output
  5. 05Open the trajectory viewer
  6. 06Offer desktop-tool and dev-UI follow-ups

Use cases

  1. 01Set up the demo on a first run
  2. 02Test browser automation without desktop input
  3. 03Inspect screenshots and model instructions from a run

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/anthropics/claude-quickstarts --skill first-run

After installing, type/first-runin Claude Code to confirm it loaded.

Details

From the project README

First run

Walk the user through running this demo for the first time. Be conversational and pause for confirmation between phases; the goal is that they understand what each step does, not just that the commands succeed.

0. Orient

Briefly say what is about to happen: you will check their setup, run one safe browser-only task that does not touch their mouse or keyboard, and then open the trajectory viewer so they can see what the model saw.

1. Environment check

Never read the contents of .env. Do not cat, grep (without -q), Read, or otherwise display it — the user's API key must never appear in this conversation or in your context. Only check for its presence.

  • Confirm a virtual environment is active and dependencies are installed: python -c "import computer_use, playwright; print('ok')". If that import fails, point them at the Installation section of README.md and stop.
  • Confirm .env exists and the API key is set without ever printing it: [ -f .env ] && grep -q '^ANTHROPIC_API_KEY=.' .env && echo 'API key: set' || echo 'API key: missing' If missing, copy .env.example to .env and ask the user to open it in their own editor and paste their key into it (do not ask them to paste the key into chat, and do not edit .env for them). Wait until they confirm.
  • Run the macOS permission preflight non-fatally: python -c "from computer_use.preflight import check_and_warn; check_and_warn(require=False)" and explain any warnings. These permissions are only needed for the desktop computer tool, which the first task does not use, so it is fine to continue without them for now.

2. Run a safe browser-only task

Explain that this task uses only the headless browser tool, so nothing on their screen will move. Then run:

CU_ENABLE_COMPUTER_USE_TOOLS=false python -m computer_use \
  "Navigate to https://en.wikipedia.org/wiki/Special:Random three times, \
   take a screenshot each time, then summarize what you saw."

While it runs, narrate what the streamed output means (dim thinking text, the cyan tool-call lines, the yellow tool-result lines, the [usage] line). When it finishes, point out the trajectory: runs/... path that was printed.

3. Open the trajectory viewer

python -m streamlit run dev_ui/trajectory_viewer/app.py

Tell them to pick the newest run in the sidebar, expand the System prompt section to see exactly what the model was told, and scroll through the turns to see each screenshot inline.

4. Next steps

Offer two follow-ups and let them choose:

  • Try the desktop tool: once Screen Recording and Accessibility are granted, run python -m computer_use "open TextEdit and type hello world". Warn them again that this will move their real mouse and keyboard.
  • Explore the dev UIs: the tool panel at python -m uvicorn dev_ui.tool_panel.server:app --reload lets them call each tool by hand without the model in the loop.

End by pointing at the Configuration and Effective caching and context pruning sections of README.md for the deeper material.

Comments

Markdown supported