name: research_synthesizer
router_kit: ManagementKit
description: Guide to summarizing research findings, extracting insights and creating actionable recommendations.
metadata:
skillport:
category: research
tags: [architecture, automation, best practices, clean code, coding, collaboration, compliance, debugging, design patterns, development, documentation, efficiency, git, optimization, productivity, programming, project management, quality assurance, refactoring, research synthesizer, software engineering, standards, testing, utilities, version control, workflow] - summary

📝 Research Synthesizer

Research summary and insight extraction guide.

📋 Synthesis Process

Raw Data → Themes → Insights → Recommendations

Steps

1. Collect - Collect all sources
2. Organize - Group by themes
3. Analyze - Find patterns
4. Synthesize - Extract insights
5. Recommend - Suggest actions

🔧 Synthesis Template

# Research Synthesis: [Topic]

## Executive Summary
[1-2 paragraph summary]

## Key Findings

### Theme 1: [Theme Name]
- Finding 1.1
- Finding 1.2
> Supporting quote or data

### Theme 2: [Theme Name]
- Finding 2.1
- Finding 2.2

## Insights
1. **Insight 1**: [Explanation]
2. **Insight 2**: [Explanation]

## Recommendations
| Priority | Action     | Impact | Effort |
| -------- | ---------- | ------ | ------ |
| High     | [Action 1] | High   | Med    |
| Med      | [Action 2] | Med    | Low    |

## Sources
1. [Source 1]
2. [Source 2]

🎯 Pattern Recognition

Affinity Mapping

┌─────────────────────────────────────┐
│           Theme A                    │
│  ┌──────┐ ┌──────┐ ┌──────┐        │
│  │Note 1│ │Note 2│ │Note 3│        │
│  └──────┘ └──────┘ └──────┘        │
└─────────────────────────────────────┘

Cross-Reference Matrix

📊 Insight Framework

Good Insight Özellikleri

• Non-obvious: Yüzeysel değil
• Actionable: Aksiyon alınabilir
• Evidence-based: Kanıta dayalı
• Relevant: İş hedefine uygun

Research Synthesizer v1.1 - Enhanced

🔄 Workflow

Source: UX Research Cheat Sheet & Qualitative Data Analysis

Phase 1: Analysis (Thematic)

• [ ] Tagging: Code raw data (notes, transcripts) by "Tag"ging (e.g., "Pain Point", "Feature Request").
• [ ] Affinity Mapping: Create "Theme"s by grouping similar tags.
• [ ] AI Assistance: Use LLM to summarize large text chunks or perform sentiment analysis.

Phase 2: Synthesis (Generating Insights)

• [ ] One-Pager: Summarize each finding in a single sentence ("Users feel Y when doing X because Z").
• [ ] Confidence: State how strong the findings are (How many users said this? What is the evidence?).
• [ ] Triangulation: Cross-verify data coming from different sources (Analytics + Interview + Survey).

Phase 3: Communication

• [ ] Hierarchical: Put top 3 most important findings at the top. Provide details as attachments (Appendix).
• [ ] Visuals: Use word cloud, chart or user journey map.
• [ ] Actionable: Add a "How Might We" question or recommendation for each insight.

Checkpoints