django-verification

django-verification is a skill for Claude Code from multiplex-ai/muggle-ai-teams. It costs 31 tokens per session (2,804 once invoked), scanned A, a copy of django-verification, MIT.

A pre-release checking routine for Django, a Python web framework. It checks the environment, code style, types, migrations, tests, security settings, and readiness for deployment.

In plain words
What is it for?
Use it before code reviews, after major Django or dependency changes, and before deploying to staging or production.
Why use it?
It helps find configuration mistakes, code problems, unsafe database changes, security issues, and failing tests before a pull request or release.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the muggle-ai-teams plugin — 166 skills, 55 commands, 30 agents, 4 hooks shipped together

Good fit Use it before code reviews, after major Django or dependency changes, and before deploying to staging or production.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/multiplex-ai/muggle-ai-teams/django-verification
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 multiplex-ai/muggle-ai-teams --skill django-verification
Clone the repo
git clone --depth 1 https://github.com/multiplex-ai/muggle-ai-teams

Made for: Claude Code.

Or install muggle-ai-teams, the plugin that ships this one along with the rest of its 166 skills, 55 commands, 30 agents, 4 hooks.

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.

agentmods badge for django-verification

README.md
[![agentmods](https://agentmods.dev/badge/skills/multiplex-ai/muggle-ai-teams/django-verification/github.svg)](https://agentmods.dev/skills/multiplex-ai/muggle-ai-teams/django-verification)
Your own site
<a href="https://agentmods.dev/skills/multiplex-ai/muggle-ai-teams/django-verification"><img src="https://agentmods.dev/badge/skills/multiplex-ai/muggle-ai-teams/django-verification/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.

agentmods 80×15 button for django-verification

Your own site · 80×15
<a href="https://agentmods.dev/skills/multiplex-ai/muggle-ai-teams/django-verification"><img src="https://agentmods.dev/badge/skills/multiplex-ai/muggle-ai-teams/django-verification.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,804 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.
Origin 100% copy Near-identical to another mod 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00031 $0.02804
Opus 5.5 $0.00012 $0.01122
Sonnet 5.5 $0.00006 $0.00561
Haiku 4.5 $0.00003 $0.00280

Measured 3d ago against content hash b330cd018e55, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

django-verification 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 3d 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.

Origin

This is a copy

100% identical to django-verification — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/django-verification/SKILL.md · 470 lines

How it starts

The opening of the file, as written. The whole thing — 470 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Django Verification Loop

Run before PRs, after major changes, and pre-deploy to ensure Django application quality and security.

When to Activate

  • Before opening a pull request for a Django project
  • After major model changes, migration updates, or dependency upgrades
  • Pre-deployment verification for staging or production
  • Running full environment → lint → test → security → deploy readiness pipeline
  • Validating migration safety and test coverage

Phase 1: Environment Check

# Verify Python version
python --version  # Should match project requirements

# Check virtual environment
which python
pip list --outdated

# Verify environment variables
python -c "import os; import environ; print('DJANGO_SECRET_KEY set' if os.environ.get('DJANGO_SECRET_KEY') else 'MISSING: DJANGO_SECRET_KEY')"

If environment is misconfigured, stop and fix.

Phase 2: Code Quality & Formatting

# Type checking
mypy . --config-file pyproject.toml

# Linting with ruff
ruff check . --fix

# Formatting with black
black . --check
black .  # Auto-fix

# Import sorting
isort . --check-only
isort .  # Auto-fix

# Django-specific checks
python manage.py check --deploy

Common issues:

  • Missing type hints on public functions
  • PEP 8 formatting violations
  • Unsorted imports
  • Debug settings left in production configuration

Phase 3: Migrations

# Check for unapplied migrations
python manage.py showmigrations

# Create missing migrations
python manage.py makemigrations --check

# Dry-run migration application
python manage.py migrate --plan

# Apply migrations (test environment)
python manage.py migrate

# Check for migration conflicts
python manage.py makemigrations --merge  # Only if conflicts exist

Report:

  • Number of pending migrations
  • Any migration conflicts
  • Model changes without migrations

Phase 4: Tests + Coverage

# Run all tests with pytest
pytest --cov=apps --cov-report=html --cov-report=term-missing --reuse-db

# Run specific app tests
pytest apps/users/tests/

# Run with markers
pytest -m "not slow"  # Skip slow tests
pytest -m integration  # Only integration tests

# Coverage report
open htmlcov/index.html

Read the full file on GitHub · 470 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.

  1. 3d ago First seen · 470 lines · 31 tokens per session scan A b330cd018e55

Subscribe to this mod's changes

django-verification is a skill published in the GitHub repository multiplex-ai/muggle-ai-teams (2 stars, last pushed 2d ago), licensed MIT. It adds 31 tokens to every session and 2,804 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to django-verification, differing in 2 lines, and is treated as a copy.

Related

Other skills, from other repositories

design-ship

One-shot pipeline turning a claude.ai/design link into a pull request: scaffold via /ork:design-import, stories and specs via /ork:cover, browser verification via /ork:expect, then open the PR. Use when a design link should come back as a PR with no intermediate steps; if all you need is the components written to…

yonatangross/orchestkit · 84 tokens

a11y-engineering

Deep accessibility engineering beyond automated tooling — focus management architecture, ARIA role correctness under dynamic mutation, live-region discipline, keyboard contract specification, and manual checks for WCAG 2.2 Target Size (Minimum) (AA) and Focus Appearance (AAA enhancement), plus a stated gap against the…

eugenelim/agent-ready-repo · 119 tokens

governance-validator

Validate FCVW structure, schemas, ownership, plan states, reading routes, Markdown and wiki health, and clean-template boundaries. Use before structural closeout, after moving governed files, or when auditing the framework. Do not use to change a skill or policy's content.

Sistema2D/FrameCode-VibeWork · 59 tokens

Component Test Scaffold (Vue.js)

Generate Vue.js component test skeletons (Vue Test Utils) from specifications.

s977043/river-review · 22 tokens

PlanGate TDD Evidence Review

A checker for TDD evidence. TDD, or test-driven development, means writing a failing test before the implementation, making it pass, and then improving the code; this checker verifies records of those stages.

s977043/river-review · 68 tokens

Test Naming and Structure

Ensure tests use clear naming and cover edge cases with proper describe/it structure.

s977043/river-review · 21 tokens