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Backend Coder

Checked
diegocanepa·vlatest·backend

Generates efficient backend code in Python/Node.js based on detailed specifications, handling API integration and database interactions.

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 diegocanepa/agent-skills --skill backend-coder -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

diegocanepa

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 diegocanepa/agent-skills at 900221604d.

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

Scanned
1 file, 40 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 allows an AI agent to generate code for backend systems. It can be used to create APIs, database interactions, and server-side logic based on natural language instructions. The generated code is intended to streamline development workflows and automate repetitive tasks.

When to use it

  • You need a simple API endpoint created quickly without writing extensive boilerplate code.
  • You want to generate SQL queries for interacting with a database based on a description of the desired data retrieval or modification.
  • You're prototyping a backend service and require initial code scaffolding.
  • You have a specific server-side task that can be described in natural language, such as processing data or handling user authentication.

Key capabilities

  • Code generation for backend systems
  • API creation from instructions
  • SQL query generation
  • Server-side logic implementation

Example prompts

  • "Create an API endpoint to retrieve all users from the database."
  • "Generate a SQL query to find customers who spent more than $100 last month."
  • "Write code to handle user authentication and authorization."

Tips & gotchas

The quality of generated code depends heavily on the clarity and specificity of your prompts. Providing detailed instructions will yield better results.