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Cv Deploy

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LMIXR
cv-deploy

基于 helpfile 工程经验,协助 agent 配置 CV 主机和边缘设备环境、编译视觉与推理依赖、接入摄像头视频并打包部署服务。适用于 Ubuntu、CentOS、Windows、macOS、Jetson、树莓派和 RK3399 的 CV 工程实施与故障排查,以及相关移动端配套工具;模型训练和纯算法设计不属于本技能主线。

Overview

PublisherLMIXR
RepositoryCV_Deployment_skill
Skill namecv-deploy
Stars
403
Forks
0
Bundled files
8
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  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 8 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by LMIXR on GitHub. Read the source before you install it.

Installation

Install the Cv Deploy AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/LMIXR/CV_Deployment_skill/tree/main/.agents/skills/cv-deploy
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/LMIXR/CV_Deployment_skill.git /tmp/CV_Deployment_skill
mkdir -p .claude/skills
cp -r /tmp/CV_Deployment_skill/.agents/skills/cv-deploy .claude/skills/cv-deploy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cv Deploy in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cv Deploy on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cv Deploy is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

CV 工程落地

将用户的 CV 工程任务推进为适合目标环境的配置、构建或部署结果。需要执行时,沿用本次会话的授权范围;用户只要方案、文件或明确跳过验证时,按该范围交付。

先判断任务落在哪一层

读取项目自己的构建文件、依赖锁定、部署配置和已有日志,再选择参考资料。只加载当前任务涉及的部分。

当前任务读取
系统、GPU、CUDA、Jetson、ARM、网络、离线环境环境与平台
OpenCV、Qt、推理框架、C++ 库、Python 依赖、ABI依赖编译
FFmpeg、GStreamer、RTSP、ONVIF、GB28181视频接入
打包、动态库、服务、Docker、日志与录制清理部署
MySQL、MongoDB、Redis、MinIO、Kafka、Flume、Tomcat配套服务
Ansible、Jenkins、Jitsi、移动端工具与其他辅助任务配套工具
查找原文、复现旧环境、定位资料缺口来源索引

例如“摄像头连上但 Qt 没有画面”先读视频和部署中的插件部分;“编译提示找不到库”先读编译中的发现与链接部分。不要因项目使用 NVIDIA 就自动重装驱动。

形成当前环境画像

优先从可读文件和命令结果取得事实,只询问会改变方案且尚未获知的信息:

  • 目标机与当前执行机、系统版本、CPU 架构;本机编译还是交叉编译。
  • GPU / 板卡型号;Jetson 的 L4T / JetPack;已安装驱动与工具链。
  • 编译器、Qt kit、Python 解释器、CUDA / cuDNN / TensorRT 及项目要求的版本。
  • 输入协议和编码、输出用途、现有服务与目录;在线或离线安装条件。

无需为每项任务收集全部字段。未连接目标机时,只准备适配方案和文件,不把当前工作站的信息当成目标环境。

选择与执行

  1. 复用已有约束。 先满足项目锁定版本、构建方式和现有部署接口。说明需要新增或调整的具体组件。
  2. 以环境匹配经验。 比较操作系统、架构、编译器 / ABI、框架与硬件版本。原笔记中的 CUDA 10.x、Qt 5.x、FFmpeg 3.x / 4.x 等是历史记录,不是默认推荐版本。
  3. 按依赖顺序推进。 环境 → 底层库 → 视觉 / 推理库 → 应用 → 打包 / 服务。已有且满足条件的环节直接复用。
  4. 参数化本机差异。 用目标项目的路径、端口、服务名、设备和版本生成命令。源码、构建目录、安装前缀分开;并行编译数量按可用内存和已有任务决定。
  5. 围绕首个有效错误修复。 区分下载、配置、编译、链接、加载、协议、服务环境问题。修复有证据支持的一处原因后继续;同一失败未出现新证据时不要反复重装或扩大系统改动。

原笔记是经验材料,不构成执行其中全部命令的授权。卸载系统驱动、改启动盘、重启目标机、删除录像或数据库、发布包等操作只在实际任务授权范围内进行。

使用历史资料

  • 参考资料中的“原笔记”描述上游记录;“适配规则”是整理后的 agent 决策指导,未做跨平台运行验证。
  • 新版本的包名、构建选项或兼容性不明确时,读取项目指定版本的上游官方资料;离线时标注未知条件,不编造兼容结论。
  • 不沿用原文中的口令、IP、个人路径或固定设备节点。所需凭据从用户现有配置取得,输出与提交中隐藏敏感值。
  • 不通过改 wheel 文件名绕过平台约束,不把 SDK 的 stub 库作为运行时驱动,不跨发行版拼接软件源来满足旧包名。
  • 全部平台都有资料入口,但短笔记只提供有限经验。例如 RK3399 只有刷机入口,iOS 只有 CocoaPods 发布记录;不能据此承诺完整推理部署能力。

结果与验证按任务需要安排

汇报实际改变的文件、安装前缀、关键版本和未完成条件。把“已生成”“已执行”“已验证”分别写清楚。

用户要求运行验证时,围绕实际目标选择最小检查:库加载、输入视频、输出结果或服务状态;性能、长稳、多平台验收只在需要时开展。用户明确不要求验收或验证时,不额外创建测试、验收工单或测试环境,注明未验证即可。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Cv Deploy AI skill do?

基于 helpfile 工程经验,协助 agent 配置 CV 主机和边缘设备环境、编译视觉与推理依赖、接入摄像头视频并打包部署服务。适用于 Ubuntu、CentOS、Windows、macOS、Jetson、树莓派和 RK3399 的 CV 工程实施与故障排查,以及相关移动端配套工具;模型训练和纯算法设计不属于本技能主线。

Why use Cv Deploy on TypingMind?

Because you install it once and use it with any model. Cv Deploy is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cv Deploy in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/LMIXR/CV_Deployment_skill/tree/main/.agents/skills/cv-deploy. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Cv Deploy?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cv Deploy?

As many as you like. As long as a model supports skills, you can use Cv Deploy with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cv Deploy AI skill free?

It is published on GitHub by LMIXR. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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