User Research Synthesis
This skill synthesizes user research data into actionable insights, saving time and ensuring key findings aren't missed.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add user-research-synthesis npx -- -y @trustedskills/user-research-synthesis
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"user-research-synthesis": {
"command": "npx",
"args": [
"-y",
"@trustedskills/user-research-synthesis"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
The user-research-synthesis skill enables AI agents to analyze and summarize qualitative user research data, such as interviews or surveys. It identifies common themes, pain points, and insights from unstructured feedback, providing actionable summaries that help guide product development and user experience improvements.
When to use it
- After conducting customer interviews to extract key takeaways
- When analyzing survey responses for patterns or trends
- To synthesize large volumes of user feedback into concise reports
- Before presenting research findings to stakeholders in a clear format
Key capabilities
- Summarizes unstructured text data from user research
- Identifies recurring themes and insights
- Highlights pain points and opportunities
- Generates structured, actionable summaries
Example prompts
- "Summarize the key themes from these 10 customer interviews."
- "What are the most common complaints mentioned in this survey?"
- "Generate a report highlighting user needs based on this feedback data."
Tips & gotchas
- Ensure input data is clean and relevant to avoid skewed results.
- Use alongside other tools for deeper analysis, as synthesis alone may miss nuanced details.
Tags
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