A guide to building Python web applications with Django, FastAPI, or both. It covers Django’s admin area and database tools, Django REST Framework for APIs, Pydantic data models, and asynchronous Python web serving.

Use it to create or review Django projects, REST APIs, views, serializers, viewsets, admin customizations, async services, and deployments using servers such as Gunicorn, Uvicorn, or Daphne.

It helps structure Python web projects and make decisions about APIs, databases, authentication, asynchronous work, and deployment.

django — Skill for Claude Code by arbazkhan971/godmode

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add arbazkhan971/godmode --skill django

Clone the repo

git clone --depth 1 https://github.com/arbazkhan971/godmode

Made for: Claude Code.

Or install godmode, the plugin that ships this one along with the rest of its 132 skills, 1 command, 7 agents, 3 MCP servers.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/arbazkhan971/godmode/django/github.svg)](https://agentmods.dev/skills/arbazkhan971/godmode/django)

Your own site

<a href="https://agentmods.dev/skills/arbazkhan971/godmode/django"><img src="https://agentmods.dev/badge/skills/arbazkhan971/godmode/django/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/arbazkhan971/godmode/django"><img src="https://agentmods.dev/badge/skills/arbazkhan971/godmode/django.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,597 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits

NVIDIA SkillSpector warn 7 Sept 2026

SkillSpector: 2 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

high Tool Misuse · line 296
Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).

Fix: Validate all tool parameters against an allowlist. Reject dangerous parameter values (shell=True, --force, -rf /) and use safe defaults.
medium Excessive Agency · line 231
Skill allows unbounded resource consumption (API calls, storage, compute). Without rate limits or quotas, a compromised or misbehaving agent can cause denial-of-service or cost overruns.

Fix: Set explicit rate limits, timeouts, and resource quotas for API calls, file operations, and compute. Implement circuit breakers for runaway loops.

How audits are shown

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00035	$0.02597
Opus 5.5	$0.00014	$0.01039
Sonnet 5.5	$0.00007	$0.00519
Haiku 4.5	$0.00003	$0.00260

Measured 1mo ago against content hash 1888afd829ef, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

django scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/django/SKILL.md · 300 lines

How it starts

The opening of the file, as written. The whole thing — 300 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Django — Django & FastAPI Development

Activate When

User invokes /godmode:django
User says "Django", "Django project", "Django app"
User mentions "FastAPI", "Pydantic", "dependency injection"
User asks about "DRF", "Django REST Framework", "serializers", "viewsets"
User mentions "Django admin", "admin customization"
User asks about "ASGI", "async Django", "Uvicorn", "Daphne"
User says "django view", "views.py", "Django view for"
When /godmode:plan identifies a Python web project
When /godmode:review flags Django or FastAPI architecture issues

Workflow

Step 1: Project Assessment

Understand the Python web application context:

PYTHON WEB PROJECT ASSESSMENT:
Project: <name and purpose>
Framework: <Django | FastAPI | both (Django + FastAPI hybrid)>
Type: <monolith | microservice | API-only | full-stack with templates>
Scale: <expected RPS, team size, data volume>
Database: <PostgreSQL, MySQL, SQLite, MongoDB>
Auth: <Django auth, OAuth2, JWT, API keys>
Async needs: <WebSocket, background tasks, streaming, long-polling>
Deployment: <Gunicorn+Nginx, Docker, serverless, PaaS>
Existing code: <greenfield | existing Django project | migration>

If the user hasn't specified, ask: "Are you building with Django, FastAPI, or both? Is this an API-only service or full-stack with templates?"

Step 2: Django Project Structure

Design the Django project layout following best practices:

DJANGO PROJECT STRUCTURE:

project/
├── manage.py
├── pyproject.toml              # Dependencies, tools config (ruff, mypy)
├── config/                     # Project-level configuration
│   ├── __init__.py
│   ├── settings/
│   │   ├── __init__.py
│   │   ├── base.py             # Shared settings
│   │   ├── development.py      # Dev overrides (DEBUG=True, etc.)
│   │   ├── production.py       # Production settings (security, caching)
│   │   └── test.py             # Test settings (fast password hasher, in-memory)
│   ├── urls.py                 # Root URL configuration
│   ├── wsgi.py                 # WSGI entry point

Read the full file on GitHub · 300 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

1mo ago First seen · 300 lines · 35 tokens per session scan A 1888afd829ef

Subscribe to this mod's changes

django is a skill published in the GitHub repository arbazkhan971/godmode (27 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 2,597 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Backend and APIs Languages Python ai-agent ai-agents ai-code-review ai-skills automated-testing autonomous-coding

plugin-system

Generic plugin system for Python applications. Auto-discovery, validation, fault tolerance. Zero dependencies (Python stdlib only).

ellmos-ai/skills · 27 tokens

django-guide

Développement d'applications Python Django avec models, views, templates, ORM, admin et Django REST Framework. Se déclenche avec "Django", "Django REST", "DRF", "ORM Django", "model Django", "vue Django". Also triggers on "Django app", "Django ORM query".

khalilbenaz/claude-skills-collection · 68 tokens

django