Django Agent Skill

by microsoft

Best practices for Django web development including models, views, templates, and testing.

591 tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

2448

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/microsoft/debugpy --skill django

The instruction itself

7 sections, as written by the author

Skill: Django

Best practices for Django web development including models, views, templates, and testing.

When to Use

Apply this skill when working with Django projects — models, views, URL routing, templates, forms, admin, and management commands.

Project Structure

Follow the standard Django app layout: models.py, views.py, urls.py, admin.py, tests.py, forms.py.
Keep each app focused on a single domain concept; avoid "god apps" with unrelated models.
Use settings/base.py, settings/dev.py, settings/prod.py for environment-specific configuration.

Models

Always define __str__ on models for admin and debugging readability.
Use Meta.ordering sparingly — it adds ORDER BY to every query. Prefer explicit .order_by() on querysets.
Use database indexes (db_index=True, Meta.indexes) for fields that appear in filter() / order_by().
Prefer CharField with choices (or TextChoices / IntegerChoices) over bare strings for constrained fields.
Use F() expressions and Q() objects for complex queries to avoid race conditions and improve readability.

Views

Prefer class-based views (CBVs) for CRUD; prefer function-based views for one-off logic.
Always explicitly set queryset or override get_queryset() — never rely on mutable class-level state.
Use select_related() and prefetch_related() to avoid N+1 query problems.
Set LOGIN_URL and use @login_required / LoginRequiredMixin consistently.

Testing

Use pytest-django with @pytest.mark.django_db for database access.
Prefer TestCase or TransactionTestCase only when explicit transaction control is needed; otherwise use pytest fixtures.
Use RequestFactory or Client to test views without starting a server.
Use baker.make() (model-bakery) or factories instead of manual model construction in tests.

Pitfalls

Never do blocking I/O in async views without wrapping in sync_to_async.
Avoid importing models at module level in settings.py or urls.py (circular imports).
Never store secrets in settings.py — use environment variables.
Avoid raw SQL unless the ORM genuinely cannot express the query.

Other skills for the same job

different authors, same section of the catalogue

Webapp Testing

by anthropics

vendor ×12

Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.

6k tokens scripts

Finishing A Development Branch

by ZhanlinCui

×7

Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup

1k tokens

Test Driven Development

by w95

×7

Use when implementing any feature or bugfix, before writing implementation code

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes

10k tokens scripts

Verification Before Completion

by ZhanlinCui

×6

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.

Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.

19k tokens

How to use it

Copy the folder

Take microsoft/django from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.