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Django App Development

Checked
kentoshimizu·vlatest·backend·Apache-2.0

This skill generates Django app code snippets and basic project structures, accelerating backend development and streamlining your workflow.

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add kentoshimizu/sw-agent-skills --skill django-app-development -a claude-code
  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

kentoshimizu

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned kentoshimizu/sw-agent-skills at 5b7bafb626.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Scanned
4 files, 107 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill enables AI agents to develop Django applications. It can generate code for models, views, and templates based on user specifications. The agent is capable of creating basic CRUD (Create, Read, Update, Delete) functionality and structuring a Django project.

When to use it

  • You need a simple web application built quickly without extensive manual coding.
  • You want to prototype an idea or test a concept with a functional backend.
  • You're looking for assistance in setting up the initial structure of a Django project.
  • You require basic database interaction and templating within your application.

Key capabilities

  • Django project generation
  • Model creation (defining data structures)
  • View implementation (handling requests and responses)
  • Template development (creating dynamic web pages)
  • CRUD functionality implementation

Example prompts

  • "Create a Django app for managing a library of books, including models for Book and Author."
  • "Generate a view that displays all books from the database in a table format."
  • “Set up a basic Django project with user authentication.”

Tips & gotchas

The agent's output is best suited for relatively simple applications. Complex or highly customized features may require manual adjustments and further development after initial generation.