check-cross-layer

Validate cross-layer code changes across API, service, and storage dimensions.

Updated Mar 3, 2026

Search Tags:#architecture #checklist #verification #software-quality #code-review #multi-layer #cross-layer

Ready to run

npx skills add https://github.com/yanzhangshuai/wen-yuan --skill check-cross-layer-yanzhangshuai

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: check-cross-layer
Source: https://github.com/yanzhangshuai/wen-yuan/tree/main/.agents/skills/check-cross-layer
Command: npx skills add https://github.com/yanzhangshuai/wen-yuan --skill check-cross-layer-yanzhangshuai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Cross-layer changes often introduce bugs when dimensions across API, services, and storage are not considered. This guide provides a post-implementation safety net to ensure all relevant layers are checked after coding.

Core Features & Use Cases

Identify Change Scope and determine applicable checks across layers (API/routes, service, DB, UI).
Enforce dimensional thinking by guiding through data flow, code reuse, import paths, and consistency checks.
Use Case: After implementing a feature touching API and database, run this skill to verify that data flow and error propagation are correct and nothing was missed.

Quick Start

Run the cross-layer check on your latest change set to verify dimensions across API, service, and data layers.

Frequently Asked Questions about check-cross-layer

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

FAQPage Schema

How do I verify cross-layer changes after modifying software across multiple layers?▼

To verify cross-layer changes, you must identify the change scope across API, service, and storage layers, then apply dimensional checks for data flow and import-path consistency to prevent regressions.

What is cross-layer verification in software architecture?▼

Cross-layer verification is a post-implementation safety check that ensures all design dimensions across API routes, services, and databases are considered and validated after code modifications.

How do I check data flow and error propagation consistency across API and database layers?▼

Checking data flow and error propagation consistency requires a stepwise workflow that guides reviewers through applicable checks, ensuring code reuse and dimensional alignment between API and storage layers.

When do I need to run a multi-layer checklist for code review?▼

You need a multi-layer checklist for code review when implementing a feature that touches multiple architectural dimensions, ensuring all scope boundaries and edge cases are caught before deployment.

Does cross-layer code review work without dependencies or specific components?▼

Yes, cross-layer code review works without external dependencies or components, applying a structured guardrail workflow to guide reviewers through dimensional checks and consistency verification directly.