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System Design

Checked
qodex-ai·vlatest·other

Helps with AI, design as part of agent workflows workflows.

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 qodex-ai/ai-agent-skills --skill system-design -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

qodex-ai

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 qodex-ai/ai-agent-skills at 6ea9f00885.

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

Commit
6ea9f00885
Manifest
skills/system-design/SKILL.md
Scanned
1 file, 76 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 comprehensive system design architectures, including component diagrams, data flow models, and scalability strategies. It assists in translating high-level requirements into structured technical blueprints suitable for engineering teams.

When to use it

  • Planning the infrastructure for a new microservices-based application.
  • Designing database schemas and API endpoints for a data-heavy platform.
  • Creating high-level architecture diagrams for stakeholder presentations.
  • Evaluating scalability options for handling increased user traffic.

Key capabilities

  • Generates detailed system architecture descriptions based on functional requirements.
  • Outlines component interactions and data flow between services.
  • Suggests patterns for scalability, reliability, and maintainability.
  • Produces structured documentation suitable for technical review.

Example prompts

  • "Design a scalable system architecture for a real-time chat application supporting 100k concurrent users."
  • "Create a high-level system design diagram with component descriptions for an e-commerce platform with payment integration."
  • "Outline the data flow and database structure for a recommendation engine using machine learning models."

Tips & gotchas

Ensure you provide clear functional requirements and non-functional constraints (e.g., latency, throughput) to get accurate designs. This skill focuses on architectural concepts rather than writing production-ready code or configuring specific cloud environments directly.