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steroid-verify

Verify AI-generated code against specifications and quality standards.

3|Updated Mar 10, 2026
Search Tags:#code quality#testing#code review#CI/CD#verification#AI guardrails
One-click install
npx skills add https://github.com/nzkbuild/steroid-workflow --skill steroid-verify
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: steroid-verify
Source: https://github.com/nzkbuild/steroid-workflow/tree/main/skills/steroid-verify
Command: npx skills add https://github.com/nzkbuild/steroid-workflow --skill steroid-verify

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires @ziul285/gitleaks, knip, madge, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill ensures that AI-generated code is rigorously verified against requirements and quality standards before it can be considered complete, preventing the deployment of faulty or incomplete solutions.

Core Features & Use Cases

  • Spec Compliance: Verifies that the code meets all acceptance criteria defined in spec.md.
  • Code Quality Checks: Scans for common code smells, anti-patterns, and potential security vulnerabilities.
  • Test Execution: Runs automated tests to confirm functionality and stability.
  • Use Case: After an AI builds a new user authentication module, this Skill will automatically check if the login/logout flows work as specified, if the code is secure, and if all unit tests pass, providing a definitive "PASS", "FAIL", or "CONDITIONAL" verdict.

Quick Start

Use the steroid-verify skill to verify the 'user-auth' feature.

Frequently Asked Questions about steroid-verify

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I verify AI-generated code against project specifications before deployment?▼

Verifying AI-generated code against project specifications requires a multi-stage review process that validates spec compliance, code quality, test execution, and infrastructure integrity. This Skill cross-references acceptance criteria in spec.md and generates a definitive PASS, FAIL, or CONDITIONAL verdict in verify.md.

What is the best way to automate code quality checks and security scanning for AI-generated code?▼

Automating code quality checks for AI-generated code involves scanning for anti-patterns, code smells, and security vulnerabilities using multi-stage review protocols. This Skill integrates gitleaks, knip, and madge to enforce strict verification standards and automatically report infrastructure integrity results.

How do I ensure AI code compliance with CI/CD testing and quality standards?▼

Ensuring AI code compliance with CI/CD testing requires running automated tests to confirm functionality and stability while validating adherence to strict verification protocols. This Skill executes comprehensive test suites and outputs compliance reporting directly into verify.md.

Does steroid-verify work with dependencies like gitleaks, knip, and madge for infrastructure integrity checks?▼

Yes, steroid-verify integrates gitleaks for security vulnerability scanning, knip for code quality analysis, and madge for infrastructure integrity validation. These dependencies enable the multi-stage review process to confirm spec compliance and test execution for AI-generated solutions.

When do I need to run a comprehensive code review on AI-generated modules?▼

Running a comprehensive code review on AI-generated modules is needed immediately after generation and before deployment to prevent faulty solutions. This Skill validates acceptance criteria, executes automated tests, and checks for security vulnerabilities to provide a definitive deployment verdict.

What are the limitations of automated verification protocols for AI-generated code?▼

Automated verification protocols for AI-generated code are limited by the accuracy of the acceptance criteria defined in spec.md and the scope of configured test execution. The Skill relies on strict dependency integration with gitleaks, knip, and madge to detect code smells and infrastructure issues.

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