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Agent Skill · 前端设计

modular-monolith-architecture-fastapi(modular monolith 架构 FastAPI)

用于辅助 Python 项目开发、测试、依赖管理和常见框架工作流。它适合让 Agent 阅读 Python 代码、定位测试问题、整理运行命令、生成脚本或分析数据处理逻辑。使用时需要确认项目虚拟环境、依赖版本和测试入口;涉及执行脚本、读写文件、访问数据库或调用外部 API 时,应先明确运行目录和输入输出范围,避免误改生产数据。

modular-monolith-architecture-fastapi 是前端设计类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在前端设计类的 10,216 个 Skill 里排第 9,472。

总安装 214周安装 9GitHub Stars 公开资料未说明下载 75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
unknown

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:modular-monolith-architecture-fastapi(modular monolith 架构 FastAPI)
来源仓库:https://github.com/azzam-almatrafi/skills
仓库路径:skills/modular-monolith-architecture-fastapi
安装命令:
npx skills add https://github.com/azzam-almatrafi/skills --skill modular-monolith-architecture-FastAPI
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/azzam-almatrafi/skills --skill modular-monolith-architecture-FastAPI

这个 Skill 是做什么的

前端设计类 Skill 关注页面结构、视觉规范和组件写法,输出通常是可运行的界面代码。

modular-monolith-architecture-fastapi 用于辅助 Python 项目开发、测试、依赖管理和常见框架工作流。适合让 Agent 阅读 Python 代码、定位测试问题、整理运行命令、生成脚本或分析数据处理逻辑。

使用时需要确认项目虚拟环境、依赖版本和测试入口;涉及执行脚本、读写文件或调用外部 API 时应明确运行目录和输入输出范围。避免误改生产数据,尤其在访问数据库或调用外部服务时需格外谨慎。通过 npx skills add 命令从指定 GitHub 仓库安装,需结合原始 README 确认具体用法。

来源仓库内路径:skills/modular-monolith-architecture-fastapi

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 Codex、Claude、Cursor、Gemini CLI;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 npx skills add https://github.com/azzam-almatrafi/skills --skill modular-monolit…;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

modular-monolith-architecture-fastapi 怎么安装?

在终端执行 npx skills add https://github.com/azzam-almatrafi/skills --skill modular-monolith-architec…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

modular-monolith-architecture-fastapi 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。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。

modular-monolith-architecture-fastapi 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。

modular-monolith-architecture-fastapi 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

modular-monolith-architecture-fastapi 用的人多吗?

公开数据是累计安装 214 次,近一周安装 9 次,下载 75 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。

modular-monolith-architecture-fastapi 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

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 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

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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 Codex,想直接扩展它能力的人。
  • 需要处理前端设计类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

前端设计类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
frontend-design

前端设计 · Codex、Claude

8,823,360126,072只读MIT通过
vercel-composition-patterns

Vercel 组合模式 · Codex、Claude

3,858,81625,893需要联网MIT通过
vercel-react-native-skills

Vercel React native skills 前端 · Codex、Claude

2,468,66425,878只读MIT通过
adapt

adapt 搜索 · Codex、Claude

2,027,04023,125操作浏览器未明确通过
bolder

bolder 分析 · Codex、Claude

2,004,28823,130只读未明确通过
modular-monolith-architecture-fastapi

modular monolith 架构 FastAPI · 本页

214—需要联网未明确通过

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

FastAPI Modular Monolith Architecture — Project Scaffolder

Generate production-ready Modular Monolith projects with FastAPI, featuring proper module boundaries, async-first design, dependency injection, shared kernel, and infrastructure following industry best practices.

Overview

A Modular Monolith is a single deployable application organized into loosely coupled, highly cohesive modules — each representing a bounded context. FastAPI's speed, async capabilities, dependency injection system, and automatic API documentation make it an ideal framework for this architecture.

This skill scaffolds complete FastAPI projects with:

  • Module isolation: Each module owns its models, repositories, services, routes, schemas, and dependencies
  • Async-first design: All I/O operations use async/await (SQLAlchemy async, aiosmtplib, aiocache)
  • FastAPI dependency injection: Loose coupling via Depends() and Annotated types
  • Generic repository pattern: Base CRUD with pagination, filtering, sorting, and soft deletes
  • Inter-module communication: Via gateway contracts and domain events (fastapi-events)
  • Shared kernel (core): Cross-cutting concerns — base models, config, services, exception handling
  • Database-per-module schema: Logical isolation within a single PostgreSQL database via Alembic
  • Production-ready: Docker, Redis caching, task queues (Taskiq), structured logging, rate limiting
  • Migration-ready boundaries: Modules can be extracted to microservices later

Workflow

Step 1: Gather Requirements

If the user hasn't specified, ask for:

  1. Project name (e.g., conduit, saas-platform, ecommerce-api)
  2. Business modules (e.g., Auth, Articles, Comments, Payments, Notifications)
  3. Database preference (PostgreSQL recommended, MySQL supported)
  4. Additional features: Event bus, caching (Redis), task queue, email, Docker, CI/CD
  5. Authentication method: JWT (default), OAuth2, API keys

If the user provides $ARGUMENTS, parse them: $ARGUMENTS[0] = project name, remaining = module names.

Step 2: Generate Project Structure

Read the architecture references for FastAPI:

Generate the project following these critical rules:

Module Rules
  1. Each module gets its own directory with internal layers: models/, schemas/, repositories/, services/, routes/, dependencies/
  2. Modules communicate ONLY through gateway contracts — never import another module's internal types
  3. Each module has its own Alembic migration files
  4. Each module registers its own dependencies via Depends() functions
  5. No circular dependencies between modules
  6. Each module has its own routers.py that aggregates its versioned route files
Shared Kernel (Core) Rules
  1. Contains ONLY cross-cutting concerns: base models, configuration, database session, generic repository, API response schemas, service interfaces (cache, mail, queue, log, events), exception handlers, middlewares
  2. Must be thin — if it grows large, something belongs in a module
  3. Never contains business logic specific to any module
Infrastructure Rules
  1. Single entry point: app/main.py (FastAPI app initialization)
  2. Composition root: app/core/routers.py wires all module routers together
  3. Database session is shared but models/schemas are isolated per module
  4. Domain events via fastapi-events for async inter-module communication (upgradeable to Kafka/RabbitMQ)
  5. Background tasks via Taskiq with Redis backend

Step 3: Generate Code

For each module, generate:

  • Models layer (models/): SQLAlchemy ORM models with soft delete support
  • Schemas layer (schemas/): Pydantic v2 request/response/DTO schemas
  • Repository layer (repositories/): Data access extending BaseRepository with custom queries
  • Service layer (services/): Business logic with event dispatch and cross-cutting service calls
  • Routes layer (routes/v1/): Versioned API endpoints with FastAPI routers
  • Dependencies layer (dependencies/): DI setup for repositories, services, and auth guards
  • Gateway (gateway.py): Public interface exposing module functionality to other modules
  • Events (events.py): Domain event definitions
  • Exceptions (exceptions.py): Module-specific custom exceptions
  • Config (config.py): Module-specific configuration

Also generate:

  • Shared kernel (app/core/): Base classes, database setup, generic repository, API schemas, service interfaces, exception handlers, middlewares, dependency injection
  • Entry point (app/main.py): FastAPI app with lifespan, middleware registration, exception handlers
  • Tests: Unit tests, integration tests, factories, and architecture boundary tests — see references/testing-strategies.md
  • Docker (if requested): Dockerfile + docker-compose with PostgreSQL, Redis, Taskiq worker, and Mailhog — see references/deployment-scaling.md
  • Alembic: Migration configuration with alembic.ini and migrations/env.py
  • pyproject.toml: Dependencies managed with UV or pip
  • README.md: Architecture overview, how to run, how to add modules (use examples/README-template.md)

Step 4: Validate

After generation:

  1. Verify no module directly imports another module's internal types (only gateways)
  2. Confirm each module has its own models and migration support
  3. Check that the shared kernel (app/core/) contains no business logic
  4. Ensure the project runs successfully with uvicorn app.main:app --reload
  5. Run any generated tests with pytest

Validation scripts are available in scripts/ for CI integration:

  • scripts/validate-boundaries.sh <app-dir> — detects cross-module boundary violations in Python imports
  • scripts/validate-shared-kernel.sh <core-dir> <modules-dir> — ensures core doesn't reference modules
  • scripts/check-circular-deps.sh <app-dir> — detects circular dependencies between modules

Step 5: Migration Guidance

If the user asks about extracting modules to microservices:

  • Replace gateway contracts (in-process function calls) with HTTP/gRPC clients
  • Swap fastapi-events for Kafka/RabbitMQ for that module's events
  • Migrate module's database tables to a separate database
  • Deploy the extracted module as a standalone FastAPI service
  • Keep remaining modules as a monolith (no need to extract everything)

Key Principles to Enforce

PrincipleWhat It MeansHow to Enforce in FastAPI
High CohesionModule contains everything for its domainmodels + schemas + repos + services + routes per module
Low CouplingModules don't depend on each other's internalsCommunication only via gateway contracts
Dependency InjectionAll dependencies are explicit and injectableFastAPI Depends() with Annotated types
Async-FirstAll I/O operations are non-blockingasync def for routes, services, repositories
Repository PatternData access is abstracted behind interfacesBaseRepository[Model, Create, Update] generic class
Schema SeparationRequest/response/DTO schemas are distinctPydantic v2 models in schemas/ per module
Event-Driven CommunicationAsync inter-module messagingfastapi-events with domain event dispatch
Encapsulated DataModule owns its dataPer-module SQLAlchemy models, no cross-module FKs

Example Invocations

/modular-monolith-architecture-FastAPI conduit Auth Articles Comments
/modular-monolith-architecture-FastAPI ecommerce-api Auth Products Orders Payments
/modular-monolith-architecture-FastAPI saas-platform Auth Tenants Billing Notifications
/modular-monolith-architecture-FastAPI social-api Auth Users Posts Messages

When NOT to Use This

Suggest microservices instead if the user describes:

  • Teams needing completely independent deployment cadences
  • Requirements for polyglot tech stacks (Python ML + Go APIs + Java enterprise)
  • Extreme per-service scaling requirements
  • Already having Kubernetes infrastructure and DevOps maturity

Suggest a simple FastAPI monolith if:

  • Solo developer or very small team (1-3 devs)
  • Prototype/MVP with unclear domain boundaries
  • Application with fewer than 3 distinct business domains
  • Simple CRUD API without complex business logic

Technology Stack

CategoryTechnologyPurpose
FrameworkFastAPIWeb framework with async support
ORMSQLAlchemy 2.0 (async)Database ORM with async session
ValidationPydantic v2Request/response validation and serialization
DatabasePostgreSQLPrimary relational database
CacheRedis + aiocacheCaching with async Redis backend
MigrationsAlembicDatabase schema migrations
AuthPyJWT + Passlib (Argon2)JWT tokens + password hashing
Eventsfastapi-eventsIn-process domain event dispatcher
Task QueueTaskiq + RedisAsync background job processing
Emailaiosmtplib + Jinja2Async email with templates
LoggingstructlogStructured async logging
Testingpytest + httpx + faker + factory-boyComprehensive test suite
Package ManagerUVFast Python dependency management
LintingRuffCode linter and formatter
Type CheckingMyPyStatic type analysis
ContainerizationDocker + docker-composeDevelopment and deployment

平台分布

Codex

37.54%
按下载量换算28

Claude

31.7%
按下载量换算24

Cursor

17.64%
按下载量换算13

Gemini CLI

8.46%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

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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