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wendy-contributing温迪贡献

Agent Skill

wendy-contributing 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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

485

周安装

20

GitHub Stars

56

下载量

158
CodexClaudeCursorGemini CLI

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

unknown

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:wendy-contributing(温迪贡献)
来源仓库:https://github.com/joannis/claude-skills
仓库路径:skills/wendy-contributing
安装命令:
npx skills add https://github.com/joannis/claude-skills --skill wendy-contributing
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/joannis/claude-skills --skill wendy-contributing

简介

用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果。
  • 通过 npx skills add 命令从指定仓库安装并使用。
  • 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。
  • 可结合来源仓库和原始 README 进一步核验具体用法。

SKILL.md

WendyOS Contributing

This skill covers internal development and contribution to WendyOS itself, including building OS images, understanding agent architecture, and running E2E tests.

Overview

WendyOS is an Embedded Linux operating system for edge computing built with Yocto. It supports:

  • NVIDIA Jetson devices (production with OTA updates)
  • Raspberry Pi 4/5 (edge devices)
  • ARM64 VMs (development)

Agent Architecture

The wendy-agent is a container daemon (similar to dockerd/containerd):

  • Manages container lifecycle via gRPC on port 50051
  • Images are pushed via wendy run, not pulled from Docker Hub
  • There's no docker pull equivalent - apps are deployed from source

Building WendyOS (Yocto)

WendyOS images are built with Yocto. Three meta layers exist:

LayerTargetImage
meta-wendyos-jetsonNVIDIA Jetsonedgeos-image
meta-wendyos-virtualARM64 VMedgeos-vm-image
meta-wendyos-rpiRaspberry Pi 4/5edgeos-rpi-image

Quick build (any layer):

cd meta-wendyos-<target>
./bootstrap.sh
source ./repos/poky/oe-init-build-env build
bitbake <image-name>

For macOS, use the Docker build environment:

cd docker && ./docker-util.sh shell

See references/yocto-meta-layers.md for detailed Yocto configuration.

E2E Testing

The wendy-agent repository includes an E2E test suite in E2ETests/.

Running E2E Tests

# Start the VM
cd meta-wendyos-virtual
./scripts/setup-dev-vm.sh create && ./scripts/setup-dev-vm.sh start

# Deploy a test app first (required for container tests)
cd wendy-agent/Examples/HelloWorld
wendy run --json --device localhost:50051  # --json for non-interactive output

# Run E2E tests with fast path (CRITICAL for performance)
cd wendy-agent/E2ETests
E2E_USE_EXISTING_VM=true E2E_VM_PATH=/path/to/meta-wendyos-virtual swift test

Important: Always set E2E_USE_EXISTING_VM=true when the VM is already running. This skips shell script checks and reduces test time from ~5s/test to ~0.01s/test.

Tip: Use --json flag on all wendy commands for quick JSON responses without interactive polling.

Test Performance Tips

  • Use .serialized trait on test suites to avoid VM race conditions
  • Set E2E_USE_EXISTING_VM=true to skip redundant VM status checks
  • mDNS discovery tests take ~5s each (inherent to protocol)
  • Container state change tests can be slow - disable for quick runs
  • Don't use Issue.record() for expected failures (like WiFi in VM) - it counts as failure

CI Limitations

GitHub-hosted runners don't support nested virtualization. Use self-hosted runners or run E2E tests locally.

Test Suites

SuiteTestsTimeNotes
Device Connection7~0.07sgRPC connectivity
Container Deployment6~0.06sContainer lifecycle
WiFi Operations4~0.04sGraceful failures in VM
Hardware Capabilities4~0.07sDevice enumeration
Device Discovery4~21smDNS (slow by design)

System Internals

For debugging, container runtime details (containerd/nerdctl), mDNS discovery, device identity, and common pitfalls, see references/system-internals.md.

For Raspberry Pi specific configuration (serial console, flashing, partition layout), see references/raspberry-pi.md.

Reference Files

Load these files as needed for specific topics:

  • references/yocto-meta-layers.md - Yocto layer structure, build configuration, partition layouts, Docker build environment, common issues
  • references/system-internals.md - containerd runtime, containerd-registry, device identity, mDNS configuration, Lima VM development, offline image bundling
  • references/raspberry-pi.md - RPi machine configuration, serial console, flashing images, partition layout

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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

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

Codex

36.82%
按下载量换算58

Claude

30.18%
按下载量换算48

Cursor

18.44%
按下载量换算29

Gemini CLI

9.58%
按下载量换算15

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/joannis/claude-skills --skill wendy-contributing 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。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

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