Proj Deploy logo

Proj Deploy

Community
zhangloveyan
proj-deploy

生成Docker Compose、Dockerfile、Nginx等部署配置。用于项目初始化部署配置、新增服务需要部署、查看部署配置模板。

Overview

Publisherzhangloveyan
Repositorybackend-skill
Skill nameproj-deploy
Stars
102
Forks
31
Bundled files
8
LicenseMIT
Links
  • 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 zhangloveyan on GitHub. Read the source before you install it.

Installation

Install the Proj 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/zhangloveyan/backend-skill/tree/main/.claude/skills/proj-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/zhangloveyan/backend-skill.git /tmp/backend-skill
mkdir -p .claude/skills
cp -r /tmp/backend-skill/.claude/skills/proj-deploy .claude/skills/proj-deploy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Proj 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 Proj 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 Proj 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.

部署配置

任务文档同步

  • 确认全流程任务文档存在(如有)
  • 将部署相关文件路径记录到“扩展产物”
  • 上下文快照记录部署环境与关键约束
  • 更新下一步指令为“部署验证/回归测试”

部署架构

                    ┌─────────────┐
                    │   Nginx     │ :80/:443
                    └──────┬──────┘
           ┌───────────────┼───────────────┐
    ┌──────▼──────┐ ┌──────▼──────┐
    │ app-admin   │ │  app-api    │
    │   :9501     │ │   :9502     │
    └──────┬──────┘ └──────┬──────┘
           └───────┬───────┘
    ┌──────────────┼──────────────┐
┌───▼───┐    ┌─────▼─────┐
│ MySQL │    │   Redis   │
│ :3306 │    │   :6379   │
└───────┘    └───────────┘

目录结构

docker/
├── docker-compose.yml
├── .env
├── .env.template
├── app/
│   └── Dockerfile
├── nginx/
│   ├── nginx.conf
│   └── conf.d/
│       └── default.conf
└── scripts/
    └── deploy.sh

环境变量模板 (.env.template)

bash
PROJECT_NAME=myproject
COMPOSE_PROJECT_NAME=myproject

APP_ADMIN_PORT=9501
APP_API_PORT=9502
SPRING_PROFILES_ACTIVE=prod
JAVA_OPTS=-Xms512m -Xmx1g -XX:+UseG1GC

MYSQL_HOST=mysql
MYSQL_PORT=3306
MYSQL_DATABASE=myproject
MYSQL_ROOT_PASSWORD=change_me
MYSQL_USER=app_user
MYSQL_PASSWORD=change_me

REDIS_HOST=redis
REDIS_PORT=6379
REDIS_PASSWORD=change_me

JWT_SECRET=change_me_at_least_32_chars

TZ=Asia/Shanghai

Dockerfile

dockerfile
FROM eclipse-temurin:17-jre-alpine

WORKDIR /app

RUN apk add --no-cache tzdata \
    && cp /usr/share/zoneinfo/Asia/Shanghai /etc/localtime

ARG JAR_FILE
COPY ${JAR_FILE} app.jar

HEALTHCHECK --interval=30s --timeout=10s --retries=3 \
    CMD wget -q --spider http://localhost:${SERVER_PORT:-8080}/actuator/health || exit 1

ENTRYPOINT ["sh", "-c", "java ${JAVA_OPTS} -jar app.jar"]

Nginx 配置

nginx
upstream admin-server {
    server app-admin:9501;
}

upstream api-server {
    server app-api:9502;
}

server {
    listen 80;
    server_name localhost;

    location /{project}/web/ {
        proxy_pass http://admin-server;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
    }

    location /{project}/api/ {
        proxy_pass http://api-server;
        proxy_set_header Host $host;
        proxy_set_header X-Real-IP $remote_addr;
    }
}

常用命令

bash
# 启动
docker-compose up -d

# 停止
docker-compose down

# 查看日志
docker-compose logs -f app-admin

# 重启
docker-compose restart app-admin

# 重新构建
docker-compose up -d --build

注意事项

  1. 敏感信息 - .env 文件不要提交到 Git
  2. 端口冲突 - 确保端口未被占用
  3. 数据持久化 - 使用 volume 持久化数据
  4. 健康检查 - 配置合理的健康检查
  5. 任务文档同步 - 记录部署产物路径与验证状态

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 Proj Deploy AI skill do?

生成Docker Compose、Dockerfile、Nginx等部署配置。用于项目初始化部署配置、新增服务需要部署、查看部署配置模板。

Why use Proj Deploy on TypingMind?

Because you install it once and use it with any model. Proj 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 Proj Deploy in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zhangloveyan/backend-skill/tree/main/.claude/skills/proj-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 Proj 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 Proj Deploy?

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

Is the Proj Deploy AI skill free?

Yes. It is published on GitHub by zhangloveyan under the MIT license. 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇