Research Synthesis

anthropics/knowledge-work-pluginsOfficial

Takes messy user research data like interview transcripts, survey results, or support tickets and turns it into structured themes with quotes, user segments, and prioritized recommendations. The output format is solid: executive summary, key themes with prevalence counts, an insights-to-opportunities matrix with impact/effort scoring, and clear next steps. Works best when you have qualitative data that needs patterns pulled out. If you have analytics or a knowledge base connected, it'll cross-reference findings with usage data or pull in prior studies. The "separate observations from interpretations" tip is worth keeping in mind since it's easy to blur those lines when synthesizing.

skills.sh installs: 4.3K
GitHub stars: 35.3K
last updated: Aug 21, 2026

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Install

$ npx -y skills add anthropics/knowledge-work-plugins --skill research-synthesis --agent claude-code

Installs into .claude/skills of the current project.

Files

/research-synthesis

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.

Synthesize user research data into actionable insights. See the user-research skill for research methods, interview guides, and analysis frameworks.

Usage

/research-synthesis $ARGUMENTS

What I Accept

Interview transcripts or notes
Survey results (CSV, pasted data)
Usability test recordings or notes
Support tickets or feedback
NPS/CSAT responses
App store reviews

Output

## Research Synthesis: [Study Name]
**Method:** [Interviews / Survey / Usability Test] | **Participants:** [X]
**Date:** [Date range] | **Researcher:** [Name]

### Executive Summary
[3-4 sentence overview of key findings]

### Key Themes

#### Theme 1: [Name]
**Prevalence:** [X of Y participants]
**Summary:** [What this theme is about]
**Supporting Evidence:**
- "[Quote]" — P[X]
- "[Quote]" — P[X]
**Implication:** [What this means for the product]

#### Theme 2: [Name]
[Same format]

### Insights → Opportunities

SKILL.md on GitHub