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verification-patterns

Verify AI-generated code against scope, acceptance criteria, build, testing, and quality standards.

2|2|Updated Jan 20, 2026
Search Tags:#testing#code review#verification#compliance#reporting#ai quality
One-click install
npx skills add https://github.com/srulyt/srulys-agent-packs --skill verification-patterns
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: verification-patterns
Source: https://github.com/srulyt/srulys-agent-packs/tree/main/agent-packs/agentic-developer/.roo/skills/verification-patterns
Command: npx skills add https://github.com/srulyt/srulys-agent-packs --skill verification-patterns

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a comprehensive and standardized set of procedures for verifying the output and adherence to requirements of AI-generated code and tasks, ensuring quality and compliance.

Core Features & Use Cases

  • Structured Verification: Offers detailed, step-by-step checks for scope compliance, acceptance criteria, build, testing, and quality standards.
  • AI Artifact Detection: Includes specific patterns to identify AI-generated code segments.
  • Use Case: When an AI agent completes a coding task, this Skill can be loaded to systematically check if the code meets all specified requirements, builds correctly, passes tests, and adheres to quality standards before it's merged.

Quick Start

Use the verification-patterns skill to perform a detailed check of the latest code changes against the task contract.

Frequently Asked Questions about verification-patterns

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

FAQPage Schema
How do I verify AI-generated code meets task requirements before merging?▼

You can verify AI-generated code by running structured checks for scope compliance, acceptance criteria, build success, testing, and quality standards. This process systematically confirms the output meets all specified requirements before merging.

What is AI artifact detection in code review?▼

AI artifact detection in code review identifies AI-generated code segments using specific patterns. This allows developers to target automated outputs and ensure they meet compliance and quality standards.

How do I document verification results for AI task outputs?▼

Documenting verification results uses a structured report template to record findings on scope compliance, testing, and quality checks. This provides a standardized format for capturing AI task output validation details.

Can I systematically check scope compliance and acceptance criteria for AI code?▼

Yes, you can systematically check scope compliance and acceptance criteria using detailed verification procedures. These step-by-step checks ensure the generated code meets all specified task contract requirements.

Does code review automation support detecting AI artifacts?▼

Code review automation supports detecting AI artifacts by applying specific patterns to identify AI-generated code segments. This ensures automated outputs are flagged and verified against quality standards.

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