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Agent Skill · 开发

mimo(mimo 开发)

mimo 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。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。

mimo 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 6,691。

总安装 4,460周安装 184GitHub Stars 公开资料未说明下载 1,457核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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:mimo(mimo 开发)
来源仓库:https://github.com/duanc-chao/mimo
安装命令:
openclaw skills install mimo
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 mimo

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

提供MIMO技术专业知识支持无线通信系统设计。涵盖空间复用、波束成形与性能指标分析。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。适用于5G/6G基站与物联网设备开发场景。

安装命令:openclaw skills install mimo 技术细节应以最新标准文档为准mimo 属于开发类 Skill,可作为该场景下的辅助能力补充。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install mimo;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

mimo 怎么安装?

在终端执行 openclaw skills install mimo。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

mimo 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

mimo 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

mimo 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

mimo 用的人多吗?

公开数据是累计安装 4,460 次,近一周安装 184 次,下载 1,457 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

mimo 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
mimo

mimo 开发 · 本页

4,460—需要联网MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Skill Name: MIMO Systems & Wireless Architecture Specialist

Skill Description

This skill equips an Agent with deep technical expertise in Multiple-Input Multiple-Output (MIMO) technology, the cornerstone of modern wireless communications (4G LTE, Wi-Fi 5/6/7, and 5G NR). The Agent will be able to explain the physics of spatial multiplexing and diversity, differentiate between SU-MIMO and MU-MIMO, and analyze the architectural shifts required for Massive MIMO. It bridges the gap between theoretical information theory (Shannon capacity) and practical antenna deployment.

Core Instruction Set

1. Fundamental Architecture & Definition

Define MIMO not just as "more antennas," but as the exploitation of the spatial dimension to improve performance.

  • The Notation ($N_t \ imes N_r$): Explain that a "4x4 MIMO" system refers to 4 transmit antennas ($N_t$) and 4 receive antennas ($N_r$).
  • The Channel Matrix ($H$): Describe the wireless channel as a matrix $H$ where each element $h_{ij}$ represents the complex channel gain between transmit antenna $i$ and receive antenna $j$.
  • SISO vs. MIMO: Contrast Single-Input Single-Output (SISO) systems, which are limited by bandwidth and power, with MIMO systems, which utilize spatial degrees of freedom to increase capacity without additional spectrum.
2. Core Operational Mechanisms

Instruct the Agent to categorize MIMO operations into three distinct techniques:

  • Spatial Multiplexing (SM):

- Goal: Increase Data Rate (Throughput). - Mechanism: Splitting a high-rate data stream into multiple parallel low-rate streams transmitted simultaneously on the same frequency. - Capacity Gain: Theoretically increases channel capacity linearly with $\min(N_t, N_r)$.

  • Spatial Diversity:

- Goal: Increase Reliability (Link Robustness). - Mechanism: Transmitting the *same* data stream across different antennas (e.g., Space-Time Block Coding or Alamouti codes) to combat fading. If one path fades, another likely remains strong.

  • Beamforming:

- Goal: Increase Signal-to-Noise Ratio (SNR) and Coverage. - Mechanism: Adjusting the phase and amplitude of the signal at each antenna to create constructive interference in a specific direction (towards the user) and destructive interference elsewhere.

3. Evolution of MIMO Standards

Differentiate between the generations of MIMO technology:

  • SU-MIMO (Single-User): The base station communicates with only *one* user device at a time, utilizing all spatial streams for that single link.
  • MU-MIMO (Multi-User):

- Concept: The base station serves multiple users simultaneously on the same time-frequency resource. - Precoding: Explain that the transmitter uses Channel State Information (CSI) to pre-process signals, separating users spatially to minimize interference. - Downlink vs. Uplink: Downlink is a Broadcast Channel; Uplink is a Multiple Access Channel.

  • Massive MIMO:

- Scale: Utilizing very large antenna arrays (e.g., 64T64R, 128T128R, or 256 elements) at the base station. - Channel Hardening: As the number of antennas grows, the small-scale fading effects average out, making the channel deterministic and highly reliable. - Application: Essential for 5G mmWave and high-density urban environments.

4. Performance Metrics & Analysis

The Agent must be able to evaluate MIMO performance using specific metrics:

  • Spectral Efficiency: Measured in bits/second/Hz. MIMO allows for higher spectral efficiency by reusing the frequency spatially.
  • Diversity Gain: The improvement in signal reliability (reduction in Bit Error Rate) proportional to the product of transmit and receive antennas ($N_t \ imes N_r$).
  • Multiplexing Gain: The increase in data rate, proportional to the minimum of transmit and receive antennas ($\min(N_t, N_r)$).
5. Implementation Challenges

Address the practical hurdles in deploying MIMO systems:

  • Channel Estimation: The system must accurately estimate the channel matrix $H$. Inaccurate estimation leads to interference, especially in MU-MIMO.
  • Antenna Correlation: For MIMO to work effectively, the signal paths must be uncorrelated (rich scattering environment). If antennas are too close or in a Line-of-Sight (LOS) dominant environment, the capacity gains diminish.
  • Hardware Complexity: Massive MIMO requires a dedicated Radio Frequency (RF) chain for each antenna element, increasing cost and power consumption.

Troubleshooting & Common Misconceptions

"More Antennas Always Means Faster Speed"
  • Correction: Not always. If the environment lacks "multipath" (scattering objects like buildings or walls), adding antennas yields diminishing returns. MIMO thrives in rich scattering environments.
Confusing Beamforming with MIMO
  • Clarification: Beamforming is a *technique* often used *within* a MIMO system. You can have MIMO without beamforming (pure spatial multiplexing), and beamforming without MIMO (single stream focusing), but modern 5G uses both simultaneously.
"MU-MIMO is just Time Division"
  • Correction: MU-MIMO is *Spatial* Division. Unlike TDMA (Time Division), where users take turns, MU-MIMO users transmit/receive at the exact same time and frequency, separated only by their spatial signature.

Skill Extension Suggestions

Hybrid Beamforming

Instruct the Agent on the architecture used in mmWave 5G, which combines analog beamforming (phase shifters) and digital beamforming (baseband processing) to balance performance with hardware cost.

Cell-Free Massive MIMO

Explore the concept of "User-Centric" networks where a user is served by a cluster of distributed access points rather than a single cell tower, eliminating cell boundaries.

Reconfigurable Intelligent Surfaces (RIS)

Discuss the integration of "smart walls" or surfaces that can reflect signals to create artificial multipath environments, enhancing MIMO performance in indoor settings.

平台分布

OpenClaw

80.28%
按下载量换算1,170

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。目前只有一个公开来源,建议同时核对源仓库。

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