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ai-development-guide

Apply structured decision criteria and detect anti-patterns in software design reviews.

Updated Apr 19, 2026
Search Tags:#architecture#debugging#anti-patterns#code-quality#quality-assurance#decision-making#design-review
One-click install
npx skills add https://github.com/jcchikikomori/opencode-workflow --skill ai-development-guide-jcchikikomori
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-development-guide
Source: https://github.com/jcchikikomori/opencode-workflow/tree/main/skills/ai-development-guide
Command: npx skills add https://github.com/jcchikikomori/opencode-workflow --skill ai-development-guide-jcchikikomori

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Technical teams encounter challenges making consistent, well-justified technical decisions. This Skill provides structured decision criteria, anti-pattern detection, debugging techniques, and a quality-check workflow to guide engineering work.

Core Features & Use Cases

  • Structured Decision Criteria: Reuse proven guidelines to evaluate design options and trade-offs.
  • Anti-pattern Detection: Identify common design and coding pitfalls early to reduce technical debt.
  • Quality Assurance Workflow: Embed checks for static analysis, testing, and reviews into development cycles.
  • Use Case: When selecting an architecture, apply the criteria to compare options, surface risks, and document the rationale.

Quick Start

Provide a design challenge or debugging concern, and the guide will apply decision criteria and QA workflows to produce actionable recommendations.

Frequently Asked Questions about ai-development-guide

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

FAQPage Schema
How do I evaluate architectural decisions and trade-offs consistently?▼

Architectural decisions are evaluated using structured criteria to compare design options, surface risks, and document rationale. This guide provides proven guidelines to apply during design reviews, ensuring consistent technical decision-making across software projects.

What is the best way to detect anti-patterns during a design review?▼

Detecting anti-patterns involves identifying common design and coding pitfalls early to reduce technical debt. By applying structured checks during design reviews, you can proactively catch architectural flaws and coding anti-patterns before they impact code quality.

How do I structure a quality assurance workflow for static analysis and testing?▼

Structuring a quality assurance workflow involves embedding checks for static analysis, testing, and reviews into development cycles. This guide structures QA workflows to ensure code quality is continuously verified throughout the engineering process, preventing regression.

Why does my technical team struggle with consistent software debugging techniques?▼

Inconsistent debugging stems from a lack of structured techniques. This guide provides standardized debugging techniques and decision criteria to help technical teams resolve issues systematically during debugging sessions and quality assurance workflows.

Can I apply this guide to quality assurance workflows for any software project?▼

Yes, the guide applies to design reviews, architectural decisions, debugging sessions, and quality assurance workflows across software projects. It provides structured criteria and anti-pattern detection adaptable to various software engineering contexts.

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