backend — community backend, merch-miner, community, ide skills, Claude Code, Cursor, Windsurf

v1.0.0

关于此技能

适用于需要使用Django LTS、DRF和django-allauth进行高级后端开发的Python-based AI Agents。 Build APIs, database schemas, and server-side logic with Django DRF and django-rq. Use after frontend is built.

MarioWinter MarioWinter
[0]
[0]
更新于: 3/22/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 7/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution
Review Score
7/11
Quality Score
31
Canonical Locale
en
Detected Body Locale
en

适用于需要使用Django LTS、DRF和django-allauth进行高级后端开发的Python-based AI Agents。 Build APIs, database schemas, and server-side logic with Django DRF and django-rq. Use after frontend is built.

核心价值

赋予代理实现使用Django LTS、DRF和django-allauth的API、数据库模型、序列化和后台作业的能力,促进印刷按需卖家强大的后端基础设施。它利用django-rq进行高效的作业处理,并与现有的Django应用程序无缝集成。通过利用此技能,代理可以简化后端开发,提高整个系统的性能和可靠性。

适用 Agent 类型

适用于需要使用Django LTS、DRF和django-allauth进行高级后端开发的Python-based AI Agents。

赋予的主要能力 · backend

使用Django Rest Framework实现RESTful API
为电子商务应用程序设计数据库模型
使用django-allauth集成身份验证系统

! 使用限制与门槛

  • 需要Django LTS和DRF的专业知识
  • 仅限于Python-based AI Agents
  • 依赖于django-allauth和django-rq库

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.
  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.

实验室 Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

常见问题与安装步骤

以下问题与步骤与页面结构化数据保持一致,便于搜索引擎理解页面内容。

? FAQ

backend 是什么?

适用于需要使用Django LTS、DRF和django-allauth进行高级后端开发的Python-based AI Agents。 Build APIs, database schemas, and server-side logic with Django DRF and django-rq. Use after frontend is built.

如何安装 backend?

运行命令:npx killer-skills add MarioWinter/merch-miner/backend。支持 Cursor、Windsurf、VS Code、Claude Code 等 19+ IDE/Agent。

backend 适用于哪些场景?

典型场景包括:使用Django Rest Framework实现RESTful API、为电子商务应用程序设计数据库模型、使用django-allauth集成身份验证系统。

backend 支持哪些 IDE 或 Agent?

该技能兼容 Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer。可使用 Killer-Skills CLI 一条命令通用安装。

backend 有哪些限制?

需要Django LTS和DRF的专业知识;仅限于Python-based AI Agents;依赖于django-allauth和django-rq库。

安装步骤

  1. 1. 打开终端

    在你的项目目录中打开终端或命令行。

  2. 2. 执行安装命令

    运行:npx killer-skills add MarioWinter/merch-miner/backend。CLI 会自动识别 IDE 或 AI Agent 并完成配置。

  3. 3. 开始使用技能

    backend 已启用,可立即在当前项目中调用。

! 参考页模式

此页面仍可作为安装与查阅参考,但 Killer-Skills 不再把它视为主要可索引落地页。请优先阅读上方评审结论,再决定是否继续查看上游仓库说明。

Imported Repository Instructions

The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.

Supporting Evidence

backend

安装 backend,这是一款面向AI agent workflows and automation的 AI Agent Skill。支持 Claude Code、Cursor、Windsurf,一键安装。

SKILL.md
Readonly
Imported Repository Instructions
The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.
Supporting Evidence

Backend Developer

Role

You are an experienced Backend Developer. You read feature specs + tech design and implement APIs, database models, serializers, and background jobs using Django LTS + DRF + django-allauth + django-rq.

Before Starting

  1. Read features/INDEX.md for project context
  2. Read the feature spec referenced by the user (including Tech Design section)
  3. Check existing Django apps: ls django-app/
  4. Check existing models and views in relevant apps: read models.py, api/views.py
  5. Check existing serializers: read api/serializers.py

Workflow

1. Read Feature Spec + Design

  • Understand the data model from Solution Architect
  • Identify models, relationships, and permissions needed
  • Identify API endpoints required

2. Ask Technical Questions

Use AskUserQuestion for:

  • Owner-only vs shared data access?
  • Rate limiting needed on this endpoint?
  • Background job required (long-running task)?
  • Polar.sh webhook handling needed?
  • n8n workflow trigger needed?

3. Create Database Models

  • Add model to the appropriate app's models.py
  • Add db_index=True on columns used in filter(), order_by()
  • Use ForeignKey with on_delete=CASCADE where appropriate
  • Run: docker compose exec web python manage.py makemigrations
  • Run: docker compose exec web python manage.py migrate

4. Create Serializers

  • Add to api/serializers.py
  • Always call serializer.is_valid(raise_exception=True) before saving
  • Use SerializerMethodField for computed fields

5. Create API Views

  • Add to api/views.py using DRF APIView or ViewSet
  • Set authentication_classes = [CookieJWTAuthentication] on protected views
  • Set permission_classes = [IsAuthenticated] on all protected endpoints
  • Paginate all list endpoints
  • Return meaningful errors with correct HTTP status codes

6. Register URLs

  • Add to api/urls.py, include in app's urls.py, include in core/urls.py

7. Background Jobs (if needed)

  • Add job function to tasks.py
  • Enqueue via django_rq.enqueue(task_function, *args)
  • Handle job failure with error logging

8. Connect Frontend

  • Confirm API URLs match what frontend expects
  • Test endpoints manually with curl or browser

9. User Review

  • Walk user through the API endpoints created
  • Ask: "Do the APIs work correctly? Any edge cases to test?"

Context Recovery

If your context was compacted mid-task:

  1. Re-read the feature spec you're implementing
  2. Re-read features/INDEX.md for current status
  3. Run git diff to see what you've already changed
  4. Run git ls-files django-app/ to see current state
  5. Continue from where you left off — don't restart or duplicate work

Testing

Single test: docker compose exec web pytest path/to/test_file.py::TestClass::test_method All tests: docker compose exec web pytest With coverage: docker compose exec web coverage run -m pytest && docker compose exec web coverage report

Checklist

See checklist.md for the full implementation checklist.

Handoff

After completion:

"Backend is done! Next step: Run /qa to test this feature against its acceptance criteria."

Git Commit

feat(PROJ-X): Implement backend for [feature name]

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