Research Synthesis
- 2.9k installs
- 23.3k repo stars
- Updated August 5, 2026
- anthropics/knowledge-work-plugins
research-synthesis is a knowledge-work skill that turns interview, survey, and feedback data into themed insights, segments, and prioritized recommendations.
About
The research-synthesis skill distills user research inputs into actionable insights through a structured markdown report template. Accepted inputs include interview transcripts, survey CSVs, usability test notes, support tickets, NPS or CSAT responses, and app store reviews. Output sections cover executive summary, themed findings with prevalence counts and verbatim quotes, insights mapped to opportunities with impact and effort, identified user segments, prioritized recommendations, further research questions, and methodology notes separating observations from interpretations. Tips stress credible quotes, quantified prevalence like seven of ten instead of most users, and explicit limitations. When connectors are available it can pull supplemental user feedback, validate themes with product analytics, and publish to a knowledge base, referencing the user-research skill for methods and interview guides. The slash command format is /research-synthesis with arguments for pasted research data or file references.
- Structured synthesis template with themes, quotes, and prevalence counts.
- Insights to opportunities table with impact and effort columns.
- User segment table with characteristics, needs, and size estimates.
- Observation versus interpretation separation in methodology notes.
- Optional connector hooks for feedback, analytics, and knowledge base publish.
Research Synthesis by the numbers
- 2,910 all-time installs (skills.sh)
- +106 installs in the week ending Aug 5, 2026 (Skillselion tracking)
- Ranked #193 of 3,282 Productivity & Planning skills by installs in the Skillselion catalog
- Security screen: LOW risk (skills.sh audit)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
research-synthesis capabilities & compatibility
- Capabilities
- themed finding extraction with quote evidence · insights to opportunities impact effort mapping · user segment identification tables · prioritized recommendation ranking · methodology and bias limitation notes · optional connector enrichment for feedback and a
- Use cases
- research · planning · project management
- Pricing
- Free
What research-synthesis says it does
Separate observations from interpretations
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| Installs | 2.9k |
|---|---|
| repo stars | ★ 23.3k |
| Security audit | 3 / 3 scanners passed |
| Last updated | August 5, 2026 |
| Repository | anthropics/knowledge-work-plugins ↗ |
How do I convert raw user research transcripts and survey results into actionable product themes without losing evidence?
Synthesize interview transcripts, surveys, usability notes, and feedback into themes, segments, and prioritized recommendations.
Who is it for?
Product and research teams summarizing interviews, surveys, usability tests, or VOC feedback into decision-ready docs.
Skip if: Skip for running new interviews, statistical survey design only, or engineering implementation without research inputs.
When should I use this skill?
User has transcripts, survey results, usability notes, tickets, or NPS data needing thematic synthesis and recommendations.
What you get
A synthesis report with quoted themes, opportunity mapping, user segments, ranked recommendations, and methodology caveats.
- themed research synthesis
- prioritized product recommendations
- user segments
By the numbers
- Processes 5 input types: interview transcripts, survey results, usability notes, support tickets, and NPS responses
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 $ARGUMENTSWhat 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.
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What inputs does research-synthesis accept?
Interview transcripts, survey CSVs, usability notes, support tickets, NPS or CSAT responses, and app store reviews.
How should themes show credibility?
Include direct participant quotes, prevalence counts like X of Y participants, and separate observations from interpretations.
What optional connectors help?
User feedback for supplemental tickets, product analytics to validate themes, and knowledge base publish for repository storage.
Is Research Synthesis safe to install?
skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.