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Engineering Backend Architect

Checked
peterhdd·vlatest·backend·MIT

Designs scalable, resilient, and efficient backend systems using modern technologies based on provided requirements and constraints.

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 peterhdd/agent-skills --skill engineering-backend-architect -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

peterhdd

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 peterhdd/agent-skills at 0c9ba14756.

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

Scanned
8 files, 1,551 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 AI agents to design and architect backend systems. It can generate system diagrams, define API endpoints, and suggest appropriate technologies for a given project's requirements. The agent is capable of considering scalability, security, and maintainability when making architectural decisions.

When to use it

  • Designing the backend infrastructure for a new web application.
  • Refactoring an existing monolithic architecture into microservices.
  • Evaluating different technology stacks (e.g., Node.js vs. Python/Django) for a specific project.
  • Creating documentation and diagrams outlining the system's components and interactions.

Key capabilities

  • System diagram generation
  • API endpoint definition
  • Technology stack recommendations
  • Scalability considerations
  • Security best practices

Example prompts

  • "Design a backend architecture for an e-commerce platform using microservices."
  • "Suggest technologies for building a REST API that handles user authentication and data storage."
  • “Create a system diagram illustrating the interaction between the frontend, backend, and database.”

Tips & gotchas

The agent's recommendations are based on general best practices. Always review and adapt suggestions to your specific project context and constraints.