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research-synthesis

Synthesize user research data into themes, insights, and prioritized recommendations.

3|Updated Jun 29, 2026
Search Tags:#insights#user research#synthesis#themes#ux research#interview analysis#survey results
One-click install
npx skills add https://github.com/ruskicoder/system-prompts --skill research-synthesis-ruskicoder
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: research-synthesis
Source: https://github.com/ruskicoder/system-prompts/tree/main/prompt-orchestrator/.opencode/skills/research-synthesis
Command: npx skills add https://github.com/ruskicoder/system-prompts --skill research-synthesis-ruskicoder

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Raw user research data such as interview transcripts, survey results, and support tickets is difficult to distill into actionable product decisions. This Skill structures that raw data into themes, user segments, and prioritized recommendations. ## Core Features & Use Cases - Theme Extraction: Identifies recurring patterns across interviews, surveys, usability tests, support tickets, and NPS responses with supporting participant quotes. - Structured Output Template: Produces a consistent synthesis document with executive summary, insights-to-opportunities mapping, user segments, and prioritized recommendations. - Connector Integration: Optionally pulls support tickets, product analytics, and prior research from connected knowledge bases to validate findings. - Use Case: After conducting 10 user interviews, paste the transcripts and receive a synthesis report with prevalence counts, direct quotes, and a ranked list of product opportunities. ## Quick Start Ask the AI to run /research-synthesis on your pasted interview transcripts or survey results to generate a structured synthesis report.

Frequently Asked Questions about research-synthesis

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

FAQPage Schema
How do I synthesize user interview transcripts into themes?▼

Paste your interview transcripts or notes as input to the research-synthesis command. It identifies recurring themes with prevalence counts, supporting participant quotes, and implications for the product, then maps insights to opportunities.

What types of research data can I analyze with this skill?▼

It accepts interview transcripts, survey results in CSV or pasted form, usability test notes, support tickets, NPS and CSAT responses, and app store reviews. Multiple data sources can be combined in one synthesis.

Can research synthesis include quantitative survey data?▼

Yes, survey results in CSV or pasted format are accepted alongside qualitative data. The skill quantifies findings where possible, reporting specifics like "7 of 10 users" rather than vague claims.

What output format does the research synthesis produce?▼

It produces a markdown report containing an executive summary, key themes with evidence quotes, an insights-to-opportunities table, user segments, prioritized recommendations, open research questions, and methodology notes.

What are the limitations of automated research synthesis?▼

The synthesis quality depends on the input data provided; it does not conduct interviews or collect data itself. Findings should note methodology limitations and biases, and qualitative insights may need validation with behavioral analytics.

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