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Browser Steel

作者 xyanmi · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install browser-steel
功能描述
Browser automation with Steel CLI as the default runtime, plus a Python Playwright fallback for custom flows. Use when the user asks to open a JS-heavy site,...
使用说明 (SKILL.md)

Browser Steel

Use Steel CLI first. Use the Python runtime only when the workflow needs selector-heavy custom logic that is awkward to express through raw CLI steps.

What CLI means here

CLI means Command Line Interface.

In this skill, it specifically means the Steel terminal commands themselves, for example:

steel scrape https://example.com
steel browser start --session demo
steel browser open https://example.com --session demo
steel browser snapshot -i --session demo

The wrapper script does not replace Steel CLI. It packages it into a more publishable, agent-friendly entrypoint:

python3 {baseDir}/scripts/main.py scrape --url https://example.com
python3 {baseDir}/scripts/main.py start-session --session demo
python3 {baseDir}/scripts/main.py browser --session demo -- snapshot -i -c

So the relationship is:

  • Steel CLI = the underlying browser command system
  • scripts/main.py = the wrapper that calls Steel CLI by default
  • Python runtime = a fallback path for custom Playwright logic when CLI steps are not enough

First checks

  1. Run the doctor command before the first real task in a new environment: 
    python3 {baseDir}/scripts/main.py doctor
  2. Prefer stateless commands for one-shot extraction or capture.
  3. Prefer named sessions for multi-step interaction.
  4. Keep the same --session value across every step in one workflow.
  5. Never bake private cookies, profile names, or local paths into the skill itself.

Runtime selection

  • auto: prefer installed steel, otherwise fall back to npx @steel-dev/cli
  • cli: same as auto, but fail if no CLI path is available
  • node: force the Node-distributed CLI path through npx @steel-dev/cli
  • python: use Steel SDK + Playwright through run-python-plan

Read references/runtime-modes.md only when runtime choice or env resolution matters. Read references/official-docs.md when you need the authoritative Steel CLI or Playwright-Python upstream reference.

Preferred commands

Health check

python3 {baseDir}/scripts/main.py doctor

Stateless commands

python3 {baseDir}/scripts/main.py scrape --url https://example.com --format markdown --json
python3 {baseDir}/scripts/main.py screenshot --url https://example.com --full-page --json
python3 {baseDir}/scripts/main.py pdf --url https://example.com --json

Named-session workflow

python3 {baseDir}/scripts/main.py start-session --session demo --stealth --json
python3 {baseDir}/scripts/main.py browser --session demo -- open https://example.com
python3 {baseDir}/scripts/main.py browser --session demo -- snapshot -i -c
python3 {baseDir}/scripts/main.py browser --session demo -- fill @e2 "hello"
python3 {baseDir}/scripts/main.py browser --session demo -- click @e5
python3 {baseDir}/scripts/main.py browser --session demo -- wait --load-state networkidle
python3 {baseDir}/scripts/main.py stop-session --session demo --json

Python Playwright plan

python3 {baseDir}/scripts/main.py run-python-plan \
  --plan-file {baseDir}/references/example-plan.json \
  --url https://example.com

Read references/python-plan.md only when the CLI path is insufficient.

Guardrails

  • Start with scrape, screenshot, or pdf when the task is stateless.
  • For interactive workflows, follow start-session -> browser commands -> stop-session.
  • After any navigation or meaningful DOM change, take a fresh snapshot -i before using another @eN ref.
  • Keep secrets in env vars or an explicit --env-file, not in the skill files.
  • Pass cookies only through --cookies-file or STEEL_BROWSER_COOKIES_FILE.
  • Use the Python runtime only for tasks that genuinely benefit from custom Playwright logic.
  • Record confirmed improvements in maintenance.log.

References

  • references/official-docs.md — upstream Steel CLI and Playwright-Python references
  • references/runtime-modes.md — runtime choice, env loading, and privacy rules
  • references/cli-workflows.md — reliable Steel CLI patterns
  • references/python-plan.md — JSON plan schema and supported actions
  • references/troubleshooting.md — install/auth/runtime recovery
安全使用建议
This skill appears to be what it claims: a CLI-first browser automation wrapper that uses a STEEL_API_KEY to talk to the Steel runtime and can fall back to Python/Playwright. Before installing or using it: (1) Treat your STEEL_API_KEY like any API secret — ensure the key's scope and permissions are appropriate and rotate it if unsure. (2) Be aware the wrapper automatically looks for .env files in your working directory and the skill directory and will merge those values into its environment — do not keep unrelated secrets in those locations if you don't want them read by the skill. (3) The wrapper may call `npx @steel-dev/cli` when a local `steel` binary is absent; npx downloads and runs code from npm at runtime, so only use that fallback in environments where you trust the upstream package. (4) Optional env vars (STEEL_BROWSER_COOKIES_FILE, STEEL_BROWSER_ENV_FILE, STEEL_BROWSER_PYTHON_BIN, STEEL_BROWSER_CLI_BIN, STEEL_BROWSER_API_URL, etc.) are supported — review and set them explicitly rather than relying on auto-discovery. (5) If you need higher assurance, inspect or run the included scripts/main.py in a sandboxed environment to confirm behavior, or require a local installation of the trusted `steel` CLI to avoid npx network pulls.
功能分析
Type: OpenClaw Skill Name: browser-steel Version: 1.0.0 The skill provides a wrapper for the Steel browser automation service, supporting both CLI and Python/Playwright runtimes. It includes high-risk capabilities such as arbitrary JavaScript execution via the 'eval' action in the Python plan runner (scripts/main.py) and the use of 'npx --yes' to dynamically execute the '@steel-dev/cli' package. While these features are aligned with the stated purpose of advanced browser automation, they provide a significant mechanism for exploitation if the agent is targeted by prompt injection. No evidence of intentional malice or unauthorized data exfiltration was observed.
能力评估
✓ Purpose & Capability
Name/description (browser automation with Steel CLI + Python Playwright fallback) align with required binaries (steel, python3), the presence of a wrapper script, and the single required env var STEEL_API_KEY. The included CLI commands, session workflows, and Python plan runner are coherent with the stated purpose.
⚠ Instruction Scope
SKILL.md and scripts/main.py load environment variables and .env files (cwd and skill dir) and reference additional environment variables (e.g., STEEL_BROWSER_ENV_FILE, STEEL_BROWSER_COOKIES_FILE, STEEL_BROWSER_PYTHON_BIN, STEEL_BROWSER_CLI_BIN, STEEL_BROWSER_API_URL / STEEL_LOCAL_API_URL) that are not listed as required in the registry metadata. While these are plausible runtime options for configuring the wrapper, loading .env from the current working directory or skill directory can cause the skill to read local secrets unexpectedly. The instructions do warn against baking secrets into the skill, but the automatic .env loading behavior is a privacy-sensitive action worth noting.
ℹ Install Mechanism
No install spec (instruction-only plus an included wrapper script). The wrapper may invoke the CLI via an installed `steel` binary or fall back to `npx --yes @steel-dev/cli`, which will fetch code from the npm registry at runtime. Using npx implies runtime network retrieval/execution of package code (moderate risk compared to a declared, reviewed package install). This is expected for a CLI-first skill but worth awareness.
ℹ Credentials
The declared primary credential is a single STEEL_API_KEY, which is appropriate. However, the code and docs use several optional env vars and files (cookies file paths, alternate python binary, forced CLI bin, env-file variables, and API URL overrides). These extras are relevant to advanced runtime scenarios but increase the number of sensitive inputs the skill can read. None of them appears unrelated to the stated functionality, but they should be considered when setting environment context.
✓ Persistence & Privilege
The skill is not always-enabled and does not request system-wide persistence. It does read .env files and may create named sessions via the Steel CLI (normal for browser automation), but it does not modify other skills or global agent settings. Autonomous invocation is allowed by default (normal for skills) and is not by itself a reason to downgrade the verdict.
如何使用
  1. 确保已安装 OpenClaw（本地或 Docker 部署）
  2. 在对话框中输入安装命令：/install browser-steel
  3. 安装完成后，直接呼叫该 Skill 的名称或使用 /browser-steel 触发
  4. 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
Initial release of browser-steel skill for browser automation via Steel CLI and Python Playwright fallback. - Enables JS-heavy site automation, live page capture, screenshots, PDFs, form filling, and session workflows. - Steel CLI is used by default for most tasks; Python Playwright serves as fallback for advanced flows. - Supports stateless commands and multi-step session management. - Allows runtime selection between auto, cli, node, or python modes. - Includes guardrails for session, secret, and environment management.
元数据
Slug browser-steel
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Browser Steel 是什么？

Browser automation with Steel CLI as the default runtime, plus a Python Playwright fallback for custom flows. Use when the user asks to open a JS-heavy site,... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 103 次。

如何安装 Browser Steel？

在 OpenClaw 或 Claude Code 对话框中运行命令「/install browser-steel」即可一键安装，无需额外配置。

Browser Steel 是免费的吗？

是的，Browser Steel 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。

Browser Steel 支持哪些平台？

Browser Steel 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。

谁开发了 Browser Steel？

由 xyanmi（@xyanmi）开发并维护，当前版本 v1.0.0。

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