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Django

Checked
ar4mirez·vlatest·backend·MIT

Django provides powerful backend development capabilities for creating robust web applications and APIs, streamlining server-side logic.

Repository

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 ar4mirez/samuel --skill django -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

ar4mirez

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 ar4mirez/samuel at 571d3d1834.

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

Commit
571d3d1834
Manifest
.claude/skills/django/SKILL.md
Scanned
4 files, 2,848 lines
Copies in repo
2 — all of them scanned
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 allows AI agents to interact with and manipulate Django projects. It can generate basic project structures, create models, and handle common development tasks within a Django environment. The agent can also assist in managing settings and deploying simple applications.

When to use it

  • Rapid prototyping: Quickly scaffold a new Django project for testing or demonstration purposes.
  • Model generation: Automatically create Django model definitions based on provided data structures.
  • Simple application deployment: Assist with the process of deploying a basic Django web application.
  • Code scaffolding: Generate boilerplate code for views, forms, and templates within an existing project.

Key capabilities

  • Project scaffolding
  • Model creation
  • Settings management
  • Basic deployment assistance

Example prompts

  • "Create a new Django project named 'myproject'."
  • "Generate a model called 'Product' with fields for name, description, and price."
  • "Help me deploy my Django app to a test server."

Tips & gotchas

This skill assumes some familiarity with the Django framework. Complex deployments or customizations may require manual intervention beyond the agent’s capabilities.