本文へ移動
cccskills
無料GitHub で公開

browser-use

Use this self-contained Browser Use repo skill for Python agents that automate websites, browser sessions, custom tools, LLM/provider setup, persistent CLI sessions, cloud/sandbox production deployment, MCP, skills, and troubleshooting. Prefer ChatBrowserUse by default and route to focused sub-skills for implementation details.

インストール方法を見る

含まれるファイル(36)

  • SKILL.md5.7 KB
  • references/development-and-troubleshooting.md2.5 KB
  • references/installation-and-environment.md2.3 KB
  • references/repo-provenance.md2.8 KB
  • references/repo-routing-metadata.json504 B
  • scripts/inspect_browser_use_api.py2.5 KB
  • sub-skills/agent-programming/references/agent-api.md11.3 KB
  • sub-skills/agent-programming/references/troubleshooting.md8.5 KB
  • sub-skills/agent-programming/references/workflows.md8.9 KB
  • sub-skills/agent-programming/SKILL.md10.3 KB
  • sub-skills/browser-control/references/browser-api.md8.8 KB
  • sub-skills/browser-control/references/browser-recipes.md7.1 KB
  • sub-skills/browser-control/references/security-and-dom.md6.6 KB
  • sub-skills/browser-control/references/troubleshooting.md7.2 KB
  • sub-skills/browser-control/SKILL.md7.7 KB
  • sub-skills/cli-and-sessions/references/cli-reference.md9.8 KB
  • sub-skills/cli-and-sessions/references/session-recipes.md8.8 KB
  • sub-skills/cli-and-sessions/references/troubleshooting.md10.1 KB
  • sub-skills/cli-and-sessions/scripts/cli_smoke.sh2.5 KB
  • sub-skills/cli-and-sessions/SKILL.md10.3 KB
  • sub-skills/llm-and-output/references/cost-and-fallbacks.md7.6 KB
  • sub-skills/llm-and-output/references/models-and-credentials.md7.1 KB
  • sub-skills/llm-and-output/references/structured-output.md7.3 KB
  • sub-skills/llm-and-output/references/troubleshooting.md8.7 KB
  • sub-skills/llm-and-output/SKILL.md9.6 KB
  • sub-skills/production-integrations/references/cloud-and-sandbox.md8.2 KB
  • sub-skills/production-integrations/references/integrations-and-monitoring.md3.4 KB
  • sub-skills/production-integrations/references/mcp-and-skills.md8.0 KB
  • sub-skills/production-integrations/references/troubleshooting.md2.8 KB
  • sub-skills/production-integrations/SKILL.md9.5 KB
  • sub-skills/tools-and-actions/references/custom-tools.md7.4 KB
  • sub-skills/tools-and-actions/references/default-actions.md5.9 KB
  • sub-skills/tools-and-actions/references/security-and-files.md5.8 KB
  • sub-skills/tools-and-actions/references/troubleshooting.md6.8 KB
  • sub-skills/tools-and-actions/scripts/validate_custom_tool.py7.2 KB
  • sub-skills/tools-and-actions/SKILL.md8.4 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Browser Use Repo Skill

Browser Use is a Python >=3.11 library and CLI for AI agents that control Chromium/CDP browsers, extract page content, call LLMs, and run browser automation locally or in Browser Use Cloud.

Use this root skill as a router. Read only the sub-skill needed for the user's task, then follow its linked references/scripts.

First Checks

Read references/repo-provenance.md before deciding whether this skill matches a current checkout. If the commit, dirty paths, package version, or public entry points differ, refresh this skill from repository evidence.

Install and smoke-check a normal user environment with uv:

uv venv --python 3.11
source .venv/bin/activate
uv pip install "browser-use[cli]"
uvx browser-use install
python - <<'PY'
from browser_use import Agent, Browser, BrowserProfile, ChatBrowserUse, Tools, ActionResult
print('browser-use imports ok')
PY

For the Rust-powered beta/native runtime, install the documented native core extra when the platform wheel is available:

uv pip install "browser-use[core]"

Do not replace user-provided model names. When recommending a default for browser automation, prefer ChatBrowserUse() because it is optimized for Browser Use tasks.

Route by User Request

User requestRead
Python Agent(...), beta agent, task prompts, agent.run(), callbacks, history, initial actions, skills, planning, flash mode, max steps/timeoutssub-skills/agent-programming/SKILL.md
Browser, BrowserSession, BrowserProfile, local/real Chrome, CDP URL, cloud browser, proxies, domains, downloads, HAR/video, DOM, screenshots, Actor APIssub-skills/browser-control/SKILL.md
Custom Tools/Controller actions, default actions, ActionResult, parameter injection, file tools, sensitive data, upload/download guardrailssub-skills/tools-and-actions/SKILL.md
ChatBrowserUse, OpenAI/Google/Anthropic/other providers, structured output, extraction LLMs, fallback models, token/cost trackingsub-skills/llm-and-output/SKILL.md
Terminal browser-use/bu CLI navigation, state/click/type/upload/screenshot, sessions, profiles, cloud connect, tunnels, config, doctor/setup/initsub-skills/cli-and-sessions/SKILL.md
@sandbox, Browser Use Cloud API, profile sync, MCP server/client, hosted skills, telemetry, Slack/Discord/email/webhook integrationssub-skills/production-integrations/SKILL.md

Shared References and Scripts

  • Read references/installation-and-environment.md for package extras, environment variables, Chromium install, telemetry opt-out, and contributor setup notes.
  • Read references/development-and-troubleshooting.md for cross-cutting install/import/browser dependency failures and repo-maintainer commands.
  • Run scripts/inspect_browser_use_api.py to check imports, signatures, package version, and CLI availability in a target Python environment.

Common Defaults

  • Use ChatBrowserUse() unless the user already chose another model.
  • Load secrets from environment variables or a secret manager, not prompts or committed files.
  • Use Browser(use_cloud=True) when the user asks how to improve Browser performance in production; it provisions an optimized Browser Use Cloud browser when BROWSER_USE_API_KEY is set.
  • Add allowed_domains when the workflow handles credentials, private data, uploads, or authenticated sessions.
  • Use Pydantic v2 models for structured outputs and custom action schemas.
  • Use uv for development and installation commands.

Minimal Python Agent

import asyncio
from browser_use import Agent, ChatBrowserUse

async def main():
    agent = Agent(task="Find the top Hacker News story title", llm=ChatBrowserUse())
    history = await agent.run(max_steps=20)
    print(history.final_result())

asyncio.run(main())

Minimal Browser Configuration

from browser_use import Browser

browser = Browser(
    headless=False,
    allowed_domains=["*.example.com"],
)

For production performance and stealth:

from browser_use import Browser
browser = Browser(use_cloud=True)

Minimal Custom Tool

from browser_use import ActionResult, BrowserSession, Tools

tools = Tools()

@tools.action("Ask a human for a one-time approval code")
async def ask_code(question: str, browser_session: BrowserSession) -> ActionResult:
    return ActionResult(extracted_content="Human approval required; pause and ask the user.")

The injected browser parameter must be named exactly browser_session with type BrowserSession.

Minimal CLI Workflow

browser-use doctor
browser-use open https://example.com
browser-use state
browser-use screenshot page.png
browser-use close

Use --session NAME for multiple independent browser sessions and cloud connect when a cloud browser is required.

What Not to Do

  • Do not point future agents to source checkout examples, tests, docs, or scripts as runtime dependencies; use this skill's bundled references and scripts.
  • Do not put API keys, local profile paths, cookies, or cloud profile secrets in code snippets.
  • Do not run native examples/tests that need live websites, API keys, accounts, downloads, or browsers unless the user explicitly approves the side effects.
  • Do not install broad extras like [all] unless the user's task truly needs them.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Routes 3D ResNets PyTorch video action-recognition workflows across training, inference, and data preparation.

日本語の概要は準備中です。原文の説明を表示しています。

VectorSpaceLab/AREX-Skill3322026年9月3日 更新

3ddfa

無料

Guide 3DDFA Python inference, geometry rendering, training/evaluation, and optional C++ ONNX workflows for 3D dense face alignment.

日本語の概要は準備中です。原文の説明を表示しています。

VectorSpaceLab/AREX-Skill3322026年9月3日 更新

3ddfa-v2

無料

Routes 3DDFA_V2 face-alignment setup, still-image demos, video tracking, and ONNX benchmarking workflows.

日本語の概要は準備中です。原文の説明を表示しています。

VectorSpaceLab/AREX-Skill3322026年9月3日 更新

ab3dmot

無料

Operate AB3DMOT 3D multi-object tracking workflows for KITTI and nuScenes data, tracking, evaluation, and visualization.

日本語の概要は準備中です。原文の説明を表示しています。

VectorSpaceLab/AREX-Skill3322026年9月3日 更新

Use Hugging Face Accelerate for PyTorch training-loop migration, distributed launch/configuration, DeepSpeed/FSDP/TPU backend setup, big-model inference/offload, checkpointing, tracking, and troubleshooting.

日本語の概要は準備中です。原文の説明を表示しています。

VectorSpaceLab/AREX-Skill3322026年9月3日 更新

acme

無料

Route Acme reinforcement-learning framework tasks across core loops, replay/data, JAX agents, and TensorFlow/Sonnet agents.

日本語の概要は準備中です。原文の説明を表示しています。

VectorSpaceLab/AREX-Skill3322026年9月3日 更新

VectorSpaceLab のスキルをすべて見る

このスキルの問題を報告する