Token导航 LogoToken导航TokenDH.com
研究检索敏感数据clawhub未标认证来源可访问clear审计提醒

mijiamijia 控制

Agent Skill

mijia 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

84,549

周安装

3,488

GitHub Stars

2

下载量

27,625
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:mijia(mijia 控制)
来源仓库:https://github.com/hqman/mijia
安装命令:
openclaw skills install mijia
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install mijia

简介

控制小米米家智能家居设备。当用户想要控制台灯、智能插头或其他米家设备时,可以使用此技能。支持开/关灯、调节亮度、设置色温、切换模式等。

SKILL.md

name
mijia
description
Control Xiaomi Mijia smart home devices. Use this skill when the user wants to control desk lamps, smart plugs, or other Mijia devices. Supports turning lights on/off, adjusting brightness, setting color temperature, switching modes, and more.
invocable
true

Mijia Smart Home Control

Control Xiaomi Mijia smart devices via the mijiaAPI.

Setup

Before using this skill, you need to:

  1. Install dependencies:
cd /path/to/mijia-skill
uv sync
  1. Set your device ID as an environment variable:
export MIJIA_LAMP_DID="your_device_id"
  1. First run will prompt for Xiaomi account login via QR code.

Finding Device IDs

To find your device IDs, use the mijia-api library:

from mijiaAPI import mijiaAPI
api = mijiaAPI()
api.login()
devices = api.get_device_list()
for d in devices:
    print(f"{d['name']}: {d['did']}")

How to Use

Skill path: ~/.clawdbot/skills/mijia

Lamp Control Commands

# Navigate to skill directory
cd ~/.claude/skills/mijia

# Check status
uv run python scripts/lamp_cli.py status

# Turn on/off
uv run python scripts/lamp_cli.py on
uv run python scripts/lamp_cli.py off
uv run python scripts/lamp_cli.py toggle

# Adjust brightness (1-100%)
uv run python scripts/lamp_cli.py brightness 50

# Adjust color temperature (2700-6500K)
uv run python scripts/lamp_cli.py temp 4000

# Set mode
uv run python scripts/lamp_cli.py mode reading    # Reading mode
uv run python scripts/lamp_cli.py mode computer   # Computer mode
uv run python scripts/lamp_cli.py mode night      # Night reading
uv run python scripts/lamp_cli.py mode antiblue   # Anti-blue light
uv run python scripts/lamp_cli.py mode work       # Work mode
uv run python scripts/lamp_cli.py mode candle     # Candle effect
uv run python scripts/lamp_cli.py mode twinkle    # Twinkle alert

Natural Language Understanding

When the user says the following, execute the corresponding command:

User SaysCommand
Turn on the light / open lampscripts/lamp_cli.py on
Turn off the light / close lampscripts/lamp_cli.py off
Toggle the lightscripts/lamp_cli.py toggle
Brighter / more brightCheck status first, then increase by 20-30%
Dimmer / less brightCheck status first, then decrease by 20-30%
Full brightness / maximumscripts/lamp_cli.py brightness 100
Minimum brightnessscripts/lamp_cli.py brightness 1
Warm lightscripts/lamp_cli.py temp 2700
Cool light / white lightscripts/lamp_cli.py temp 6500
Reading modescripts/lamp_cli.py mode reading
Computer modescripts/lamp_cli.py mode computer
Night modescripts/lamp_cli.py mode night
Lamp status / what's the light statusscripts/lamp_cli.py status

Before Executing

  1. Navigate to skill directory: cd ~/.clawdbot/skills/mijia
  2. Ensure MIJIA_LAMP_DID environment variable is set
  3. Run with uv: uv run python scripts/lamp_cli.py <command>
  4. Report the result to the user after execution

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

88.48%
按下载量换算24,443

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

未展示

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills