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Dev Coding Backend

Checked
codihaus·vlatest·backend

Automates backend development tasks like API creation, database integration, and serverless function deployment using Python and Node.js.

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 codihaus/claude-skills --skill dev-coding-backend -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

codihaus

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 codihaus/claude-skills at 45dcb53286.

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

Commit
45dcb53286
Manifest
.claude/skills/dev-coding-backend/SKILL.md
Scanned
1 file, 298 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 generate and debug backend code. It can produce server-side logic, APIs, and database interactions based on natural language instructions. The skill is designed to handle common backend development tasks and assist in building robust applications.

When to use it

  • API creation: Generate API endpoints for a new feature or application.
  • Database interaction: Write code to query, update, or manage data within a database.
  • Backend logic implementation: Develop server-side functions and processes based on specific requirements.
  • Debugging existing backend code: Identify and fix errors in existing backend codebases.

Key capabilities

  • Code generation for backend systems
  • Database interaction code
  • API endpoint creation
  • Debugging assistance

Example prompts

  • "Create a Python API endpoint that returns a list of users from the database."
  • "Write a function in Node.js to authenticate a user against a MongoDB database."
  • "Debug this Java code snippet: [code snippet]"

Tips & gotchas

The skill's effectiveness depends on clear and specific instructions regarding desired functionality, programming language, and any relevant libraries or frameworks. Providing context about the existing codebase can also improve results.