research-first-development

What problem does it solve?

This Skill addresses the common issue of AI-assisted development producing inconsistent or low-quality output due to insufficient context. It provides a structured methodology to ensure that knowledge and understanding are established before implementation begins, leading to more reliable and efficient AI-driven development.

Core Features & Use Cases

• Structured Research Phase: Guides the creation of deep research documents covering competitive landscapes, technical feasibility, and core domain knowledge.
• Knowledge Encoding: Defines a process for translating research into reusable Skills, Instructions, Agents, and Prompts.
• 4-Dimension Gap Analysis: A protocol (Skills, Instructions, Agents, Prompts) to ensure comprehensive knowledge coverage before coding.
• Two-Agent Pattern: Promotes the use of distinct Builder and Validator agents for improved focus and quality.
• Synapse Hygiene: Emphasizes best practices for connecting knowledge components to prevent isolation.
• Use Case: When starting a new project or onboarding an AI to an unfamiliar domain, this Skill ensures the AI has the necessary foundational knowledge to perform effectively, preventing common pitfalls like hallucination or incorrect pattern application.

Quick Start

Initiate a new project by following the research-first development methodology, starting with competitive landscape analysis and technical feasibility research.