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Agent Skill · 研究检索

django-expert(Django expert 部署)

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。

django-expert 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 1,757。

总安装 78,336周安装 3,210GitHub Stars 56下载 25,088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

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:django-expert(Django expert 部署)
来源仓库:https://github.com/vintasoftware/django-ai-plugins
仓库路径:skills/django-expert
安装命令:
npx skills add https://github.com/vintasoftware/django-ai-plugins --skill django-expert
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/vintasoftware/django-ai-plugins --skill django-expert

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

Django 后端开发的专家指南,涵盖模型、视图、API、测试和生产部署。

涵盖模型设计、ORM 优化、查询性能调优和迁移策略,重点预防 N+1 问题 支持 Django REST Framework 开发,包括序列化器、视图集、分页、过滤和身份验证模式 包括 CSRF/XSS 预防、权限和生产就绪配置的安全最佳实践 提供生产环境的测试策略、性能分析技术和零停机部署指南

来源仓库内路径:skills/django-expert

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/vintasoftware/django-ai-plugins --skill django…;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

    它需要调用外部服务,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

django-expert 怎么安装?

在终端执行 npx skills add https://github.com/vintasoftware/django-ai-plugins --skill django-expert。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

django-expert 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。

django-expert 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

django-expert 是免费的吗?

来源标注的许可证是 MIT。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。

django-expert 用的人多吗?

公开数据是累计安装 78,336 次,近一周安装 3,210 次,下载 25,088 次,GitHub 56 星。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。

django-expert 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。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,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 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、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。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
django-expert

Django expert 部署 · 本页

78,33656调用外部服务MIT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

Django Expert

Overview

This skill provides expert guidance for Django backend development with comprehensive coverage of models, views, Django REST Framework, forms, authentication, testing, and performance optimization. It follows official Django best practices and modern Python conventions to help you build robust, maintainable applications.

Key Capabilities:

  • Model design with optimal ORM patterns
  • View implementation (FBV, CBV, DRF viewsets)
  • Django REST Framework API development
  • Query optimization and performance tuning
  • Authentication and permissions
  • Testing strategies and patterns
  • Security best practices

When to Use

Invoke this skill when you encounter these triggers:

Model & Database Work:

  • "Create a Django model for..."
  • "Optimize this queryset/database query"
  • "Generate migrations for..."
  • "Design database schema for..."
  • "Fix N+1 query problem"

View & API Development:

  • "Create an API endpoint for..."
  • "Build a Django view that..."
  • "Implement DRF serializer/viewset"
  • "Add filtering/pagination to API"

Authentication & Security:

  • "Implement authentication/permissions"
  • "Create custom user model"
  • "Secure this endpoint/view"

Testing & Quality:

  • "Write tests for this Django app"
  • "Debug this Django error/issue"
  • "Review Django code for issues"

Performance & Optimization:

  • "This Django view is slow"
  • "Optimize database queries"
  • "Add caching to..."

Production Deployment:

  • "Deploy Django to production"
  • "Configure Django for production"
  • "Set up HTTPS/SSL for Django"
  • "Production settings checklist"
  • "Configure production database/cache"

Instructions

Follow this workflow when handling Django development requests:

1. Analyze the Request and Gather Context

Identify the task type:

  • Model design (database schema, relationships, migrations)
  • View/API development (FBV, CBV, DRF viewsets, serializers)
  • Query optimization (N+1 problems, database performance)
  • Authentication/permissions (user models, access control)
  • Testing (unit tests, integration tests, fixtures)
  • Security review (CSRF, XSS, SQL injection, permissions)
  • Production deployment (settings, HTTPS, database, caching, monitoring)
  • Template rendering (Django templates, context processors)

Leverage available context:

  • If django-ai-boost MCP server is available, use it to understand project structure and existing patterns
  • Read relevant existing code to understand conventions
  • Check Django version for compatibility considerations

2. Load Relevant Reference Documentation

Based on the task type, reference the appropriate bundled documentation:

  • Models/ORM work -> references/models-and-orm.md

- Model design patterns and field choices - Relationship configurations (ForeignKey, ManyToMany) - Custom managers and QuerySet methods - Migration strategies

  • View/API development -> references/views-and-urls.md + references/drf-guidelines.md

- FBV vs CBV decision criteria - DRF serializers, viewsets, and routers - URL configuration patterns - Middleware and request/response handling

  • Performance issues -> references/performance-optimization.md

- Query optimization techniques (select_related, prefetch_related) - Caching strategies (Redis, Memcached, database caching) - Database indexing and query profiling - Connection pooling and async patterns

  • Production deployment -> references/production-deployment.md

- Critical settings (DEBUG, SECRET_KEY, ALLOWED_HOSTS) - HTTPS and SSL/TLS configuration - Database and cache configuration - Static/media file serving - Error monitoring and logging - Deployment process and health checks

  • Security concerns -> references/security-checklist.md

- CSRF/XSS/SQL injection prevention - Authentication and authorization patterns - Secure configuration practices - Input validation and sanitization

  • Testing tasks -> references/testing-strategies.md

- Test structure and organization - Fixtures and factories - Mocking external dependencies - Coverage and CI/CD integration

3. Implement Following Django Best Practices

Code quality standards:

  • Follow PEP 8 and Django coding style
  • Use Django built-ins over third-party packages when possible
  • Keep views thin, use services/managers for business logic
  • Write descriptive variable names and add docstrings for complex logic
  • Handle errors gracefully with appropriate exceptions

Django-specific patterns:

  • Use select_related() for FK/OneToOne, prefetch_related() for reverse FK/M2M
  • Leverage class-based views and mixins for code reuse
  • Use Django forms/serializers for validation
  • Follow Django's migration workflow (never edit applied migrations)
  • Use Django's built-in security features (CSRF tokens, auth decorators)

API development (DRF):

  • Use ModelSerializer for standard CRUD operations
  • Implement proper pagination and filtering
  • Use appropriate permission classes
  • Follow RESTful conventions for endpoints
  • Version APIs when making breaking changes

4. Validate and Test

Before presenting the solution:

Code review:

  • Check for N+1 query problems (use Django Debug Toolbar mentally)
  • Verify proper error handling and edge cases
  • Ensure security best practices are followed
  • Confirm migrations are clean and reversible

Testing considerations:

  • Suggest or write appropriate tests for new functionality
  • Verify test coverage for critical paths
  • Check that fixtures/factories are maintainable

Performance check:

  • Review database queries for efficiency
  • Consider caching opportunities
  • Verify proper use of database indexes

Bundled Resources

references/ - Comprehensive Django documentation loaded into context as needed

These reference files provide detailed guidance beyond this SKILL.md overview:

  • references/models-and-orm.md (~11k words)

- Model field types and best practices - Relationship configurations (ForeignKey, OneToOne, ManyToMany) - Custom managers and QuerySet methods - Migration patterns and common pitfalls - Database-level constraints and indexes

  • references/views-and-urls.md (~17k words)

- Function-based vs class-based view trade-offs - CBV mixins and inheritance patterns - URL routing and reverse resolution - Middleware implementation - Request/response lifecycle

  • references/drf-guidelines.md (~18k words)

- Serializer patterns (ModelSerializer, nested serializers) - ViewSet and router configurations - Pagination, filtering, and search - Authentication and permission classes - API versioning strategies - Performance optimization for APIs

  • references/testing-strategies.md (~18k words)

- Test organization and structure - Factory patterns vs fixtures - Testing views, models, and serializers - Mocking external services - Test database optimization - CI/CD integration

  • references/security-checklist.md (~12k words)

- CSRF protection implementation - XSS prevention techniques - SQL injection defense - Authentication best practices - Permission and authorization patterns - Secure settings configuration

  • references/performance-optimization.md (~14k words)

- Query optimization (select_related, prefetch_related, only, defer) - Database indexing strategies - Caching layers (Redis, Memcached, database cache) - Database connection pooling - Profiling and monitoring tools - Async views and background tasks

  • references/production-deployment.md (~20k words)

- Critical settings (DEBUG, SECRET_KEY, ALLOWED_HOSTS) - Database configuration and connection pooling - HTTPS/SSL configuration and security headers - Static and media file serving - Caching with Redis/Memcached - Email configuration for production - Error monitoring with Sentry - Logging and health checks - Zero-downtime deployment strategies

  • references/examples.md - Practical implementation examples

- Model design with custom managers - N+1 query optimization - DRF API endpoint implementation - Writing Django tests

Additional Notes

Django Version Compatibility:

  • Consider LTS releases (4.2, 5.2) for production
  • Check deprecation warnings when upgrading
  • Use django-upgrade tool for automated migration

Common Pitfalls to Avoid:

  • Circular imports (use lazy references)
  • Missing related_name on relationships
  • Forgetting database indexes on frequently queried fields
  • Using get() without exception handling
  • N+1 queries in templates and serializers

平台分布

Claude Code

27.3%
按下载量换算6,849

Cursor

20.51%
按下载量换算5,146

Gemini CLI

18.18%
按下载量换算4,561

Antigravity

12.8%
按下载量换算3,211

OpenCode

7.11%
按下载量换算1,784

Codex

3.47%
按下载量换算871

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。

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