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Claw Use — Device Control for AI Agents

作者 傅洋 · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install claw-use
功能描述
Control physical devices over HTTP with unified commands for screen reading, input actions, app launch, navigation, and audio output using the Claw Use proto...
使用说明 (SKILL.md)

Claw Use — Device Control for AI Agents

Give your AI agent eyes, hands, and a voice on real devices.

Claw Use is a protocol + skill for AI agents to control physical devices over HTTP. The cu CLI provides a unified interface — the same commands work across any device that implements the Claw Use API.

Supported Devices

Platform Implementation Status
Android claw-use-android ✅ Available
iOS claw-use-ios 🔮 Planned
Desktop claw-use-desktop 🔮 Planned

Prerequisites

  • cu CLI installed (ships with claw-use-android, or install standalone)
  • At least one device running a Claw Use implementation
  • Device and agent on the same network (or connected via Tailscale)

Setup

# Add a device with a friendly name
cu add redmi 192.168.0.105 \x3Ctoken>
cu add pixel 100.80.1.10 \x3Ctoken>

# List devices
cu devices
# ▸ redmi  192.168.0.105  online v1.2.0
#   pixel  100.80.1.10    offline

# Switch default
cu use pixel

# Target a specific device
cu -d redmi screenshot

Core API (all platforms)

Every Claw Use implementation exposes the same HTTP endpoints:

Perception — read the device

cu screen              # UI tree (semantic: element text, bounds, state)
cu screen -c           # compact mode (interactive elements only)
cu screenshot          # visual capture (JPEG, configurable quality)
cu notifications       # system notifications
cu status              # device health dashboard

Action — control the device

cu tap \x3Cx> \x3Cy>         # tap coordinates
cu click \x3Ctext>        # tap by visible text (semantic click)
cu type "text"         # type text (CJK supported)
cu swipe up|down|left|right
cu scroll up|down|left|right
cu back / cu home      # system navigation
cu launch \x3Capp>        # open an application
cu open \x3Curl>          # open URL
cu intent '\x3Cjson>'     # platform-specific intent (Android)

Audio

cu tts "hello"         # speak through device speaker
cu say "你好"          # alias

Device State

cu wake                # wake screen
cu lock / cu unlock    # lock/unlock (PIN required for unlock)

Workflow Patterns

Navigate and interact

cu launch org.telegram.messenger
cu screen -c                        # see what's on screen
cu click "Search"
cu type "John"
cu click "John, last seen recently"
cu type "Hey!"
cu click "Send"

Visual + semantic dual-channel

cu screen -c                         # semantic: what elements exist
cu screenshot 50 720 /tmp/look.jpg   # visual: what it actually looks like

Multi-device orchestration

cu -d phone1 launch com.whatsapp
cu -d phone2 screenshot
cu -d tablet open "https://example.com"

For Agent Developers

Claw Use is designed as a protocol, not just an app. To add support for a new platform:

  1. Implement the Claw Use HTTP API spec
  2. Expose endpoints on a configurable port (default: 7333)
  3. Support token auth via X-Bridge-Token header
  4. Return JSON responses matching the documented schemas

The cu CLI and this skill work automatically with any compliant implementation.

Tips

  • cu screen -c is the primary perception tool — compact mode filters noise
  • cu click by text is more reliable than cu tap when text is visible
  • cu screenshot when you need visual context the UI tree can't capture
  • Auto-unlock is transparent: locked devices auto-unlock before any command
  • Combine with Tailscale for remote access from anywhere
安全使用建议
This skill appears to be a genuine device-control protocol, but a few gaps warrant caution. Before installing or enabling it: 1) Confirm how authentication tokens are provided and stored — the skill mentions X-Bridge-Token but declares no required credentials; avoid giving long-lived tokens unless you trust the implementation. 2) Clarify the unlock behavior — does the agent really auto-unlock devices, and under what conditions? Auto-unlock can let the agent access locked device contents. 3) Restrict autonomous invocation or require explicit user confirmation for sensitive actions (screenshots, reading notifications, unlocking, sending intents). 4) Only use implementations you trust (verify the cu CLI source or the device-side implementation), run device control on isolated networks when possible, and avoid exposing control ports to the public internet. 5) If the publisher can provide updated metadata (declared required credentials, install instructions, and a security/privacy page), that would reduce uncertainty and could change this assessment to benign.
功能分析
Type: OpenClaw Skill Name: claw-use Version: 1.0.0 The skill bundle provides instructions for an AI agent to use the 'cu' CLI tool for remote device control. While the functionality is transparently documented and aligned with its stated purpose, it introduces high-risk capabilities such as visual screen capture (cu screenshot), reading system notifications (cu notifications), and simulating user input or keystrokes (cu type, cu tap) on connected devices. These features represent a significant attack surface if the agent is manipulated, though no evidence of intentional malice, backdoors, or unauthorized data exfiltration was found in SKILL.md or _meta.json.
能力评估
Purpose & Capability
The SKILL.md describes a coherent device-control protocol (HTTP API, cu CLI, endpoints for screen, tap, screenshot, TTS, etc.), which matches the skill name and description. However, the doc requires token-based auth (X-Bridge-Token) yet the registry metadata declares no required credentials or primaryEnv. That omission is notable: a real integration would usually declare how tokens are supplied.
Instruction Scope
Runtime instructions permit reading UI trees, screenshots, notifications, and performing input/launch actions — all expected for device control but high-impact. SKILL.md also contains a contradiction: Device State says 'unlock (PIN required for unlock)' but Tips state 'Auto-unlock is transparent: locked devices auto-unlock before any command.' That discrepancy affects security assumptions (automatic unlocking vs requiring PIN). The instructions do not limit or describe how sensitive data (screenshots, notifications) should be handled or transmitted.
Install Mechanism
This is instruction-only with no install spec or bundled code, which is low-risk from a supply chain perspective. The skill expects the 'cu' CLI to be installed but doesn't provide an install mechanism — acceptable but the absence of an official install source or guidance in metadata reduces transparency.
Credentials
The protocol requires token auth via X-Bridge-Token per the docs, but the registry metadata lists no required environment variables or primary credential. The skill also suggests optional Tailscale use for remote access (which would require separate credentials/config). Requesting no declared credentials while describing token-based auth is inconsistent and leaves unclear how secrets are expected to be supplied or stored.
Persistence & Privilege
always:false (no forced persistence). The skill can be invoked autonomously by the agent (platform default). Given this skill allows remote control of physical devices (taps, unlocks, app launches, screenshots), autonomous invocation increases risk; consider restricting autonomous use or requiring explicit user approval for commands that affect devices or capture content.
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 claw-use
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /claw-use 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: cu CLI + skill for controlling Android phones (and future devices) via HTTP API. 25 endpoints covering screen reading, screenshots, tap/click/type/swipe, TTS, intents, notifications, and device management. Multi-device support with named aliases.
元数据
Slug claw-use
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

Claw Use — Device Control for AI Agents 是什么?

Control physical devices over HTTP with unified commands for screen reading, input actions, app launch, navigation, and audio output using the Claw Use proto... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 250 次。

如何安装 Claw Use — Device Control for AI Agents?

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

Claw Use — Device Control for AI Agents 是免费的吗?

是的,Claw Use — Device Control for AI Agents 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Claw Use — Device Control for AI Agents 支持哪些平台?

Claw Use — Device Control for AI Agents 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 Claw Use — Device Control for AI Agents?

由 傅洋(@4ier)开发并维护,当前版本 v1.0.0。

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