domain-research

# Universal Research Framework

## Core Purpose

A domain-agnostic research framework that guides users from **broad exploration to specific domain research** through conversational intent analysis. Works for any field:

- Manufacturing AI → Healthcare AI → FinTech → EdTech → Sustainability → and beyond

### What It Does

1. **Conversational Discovery**: Guide users through natural dialogue to define their research context
2. **Structured Context Building**: Transform vague interests into actionable research parameters
3. **Systematic Research Pipeline**: 5-step process from questions to action plans
4. **Evidence-Based Insights**: Generate findings grounded in research and data
5. **Practical Application**: Convert insights into executable roadmaps

## Target Audience

This framework serves **domain practitioners** across any field:

- **Industry Professionals**: Engineers, managers, analysts seeking evidence-based guidance
- **Academic Researchers**: Faculty, students bridging theory and practice
- **Business Leaders**: Decision-makers needing structured research for strategy
- **Consultants**: Professionals providing research-backed recommendations
- **Policy Makers**: Those needing comprehensive domain understanding

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## Research Pipeline

### Step 0: Conversational Intent Analysis
**Prompt**: `prompts/intent-analyzer.md`
**Purpose**: Guide users from vague interests to structured research context through dialogue
**Process**:
- Open invitation → Context deepening → Synthesis → Confirmation
- Adaptive questioning based on user type (clear/vague/assigned/exploratory)
**Output**: Structured YAML research context

### Step 1: Key Question Generation
**Prompt**: `prompts/key-questions.md`
**Purpose**: Generate 5 testable, meaningful research questions
**Input**: Research context from Step 0
**Output**: Prioritized questions with importance, impact, and methodology

### Step 2: Research Gap Identification
**Prompt**: `prompts/research-gaps.md`
**Purpose**: Identi