Skip to content
TrustedSkillsbeta
Back to all skills

Architecture Validation

Checked
d-o-hub·vlatest·backend·MIT

Verifies cloud architecture designs against best practices & security standards, identifying potential risks and optimization opportunities.

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 d-o-hub/rust-self-learning-memory --skill architecture-validation -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

d-o-hub

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 d-o-hub/rust-self-learning-memory at da7210f59b.

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

Commit
da7210f59b
Manifest
.agents/skills/architecture-validation/SKILL.md
Scanned
7 files, 550 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 validates architectural designs, identifying potential issues and suggesting improvements. It can analyze diagrams, code snippets, or textual descriptions of an architecture to ensure adherence to best practices and identify areas for optimization. The skill aims to improve the robustness, scalability, and maintainability of software systems.

When to use it

  • Reviewing a new system design: Before implementation begins, validate that the proposed architecture meets requirements and avoids common pitfalls.
  • Analyzing existing codebases: Identify architectural debt or inconsistencies in legacy systems.
  • Refactoring an application: Ensure changes align with desired architectural principles.
  • Preparing for a security audit: Proactively identify potential vulnerabilities related to architectural choices.

Key capabilities

  • Architecture diagram analysis
  • Code snippet review
  • Textual description assessment
  • Best practice adherence checks
  • Optimization suggestions

Example prompts

  • "Analyze this architecture diagram and identify any potential bottlenecks."
  • "Review the following code for architectural inconsistencies with a microservices pattern: [code snippet]"
  • "Assess this textual description of our data pipeline architecture and suggest improvements for scalability."

Tips & gotchas

The skill's effectiveness depends on providing clear and detailed input. Ambiguous or incomplete information may lead to less accurate results.