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Research Synthesis

AnthropicOfficialPublished by Anthropic

  • Skill
  • Content generator
  • Business and productivity
  • Apache-2.0
  • No issues found
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From the author

Synthesize user research into themes, insights, and recommendations. Use when you have interview transcripts, survey results, usability test notes, support tickets, or NPS responses that need to be distilled into patterns, user segments, and prioritized next steps.
— the description by Anthropic

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The research-synthesis skill provides a structured framework for distilling qualitative and quantitative user data into a professional research report. It processes diverse inputs such as interview transcripts, survey results, and support tickets to identify recurring patterns, define user segments, and map findings to actionable product opportunities. By enforcing a consistent output format, it ensures that research findings are credible, evidence-based, and ready for stakeholder review.

What it does

  • Extracts key themes and patterns from raw research data
  • Generates an executive summary of research findings
  • Maps insights to specific product opportunities with impact and effort assessments
  • Identifies and characterizes distinct user segments
  • Prioritizes recommendations based on research evidence
  • Suggests follow-up questions to address knowledge gaps

When to use it

  • After completing a round of user interviews or usability testing
  • When you need to make sense of a large volume of survey or NPS responses
  • When consolidating customer support tickets to identify product pain points
  • Before planning a product roadmap to ensure features are based on user needs

Advantages

  • Standardizes the presentation of research findings
  • Encourages evidence-based decision making by linking insights to raw quotes
  • Helps distinguish between raw observations and researcher interpretations
  • Facilitates prioritization through structured impact and effort analysis

Usage examples

“Synthesize these 10 interview transcripts from our recent onboarding study.”
A structured report containing key themes, identified user segments, and a prioritized list of onboarding improvements.
“Analyze these survey results and support tickets to find the top 3 pain points.”
A summary table mapping specific user complaints to potential product opportunities and their estimated impact.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/anthropics/research-synthesis/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip research-synthesis.zip -d .agents/skills

Documentation by Anthropic

/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

| Insight | Opportunity | Impact | Effort |
|---------|-------------|--------|--------|
| [What we learned] | [What we could do] | High/Med/Low | High/Med/Low |

### User Segments Identified
| Segment | Characteristics | Needs | Size |
|---------|----------------|-------|------|
| [Name] | [Description] | [Key needs] | [Rough %] |

### Recommendations
1. **[High priority]** — [Why, based on which findings]
2. **[Medium priority]** — [Why]
3. **[Lower priority]** — [Why]

### Questions for Further Research
- [What we still don't know]

### Methodology Notes
[How the research was conducted, any limitations or biases to note]

If Connectors Available

If ~~user feedback is connected:

  • Pull support tickets, feature requests, and NPS responses to supplement research data

  • Cross-reference themes with real user complaints and requests

If ~~product analytics is connected:

  • Validate qualitative findings with usage data and behavioral metrics

  • Quantify the impact of identified pain points

If ~~knowledge base is connected:

  • Search for prior research studies and findings to compare against

  • Publish the synthesis to your research repository

Tips

  1. Include raw quotes — Direct participant quotes make insights credible and memorable.

  2. Separate observations from interpretations — "5 of 8 users clicked the wrong button" is an observation. "The button placement is confusing" is an interpretation.

  3. Quantify where possible — "Most users" is vague. "7 of 10 users" is specific.

Files

Requirements and compatibility

Written for: Claude Code, Claude apps

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Claude Code frontmatter

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Published by
Anthropic
Publisher
Anthropic (Official)
Source
anthropics/knowledge-work-plugins · design/skills/research-synthesis · commit e050c2e
Licence
Apache License 2.0 (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Anthropic.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download research-synthesis.zip