user-interview-synth
Skill1 starsChanged 7 months agoMITView on GitHub
Synthesize raw user interview notes or transcripts into structured insights. Use when processing interview notes, research sessions, usability tests, or customer calls.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- jpoindexter/theft-kittheir own version, first seen May 20, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- jpoindexter/theft-kit★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository26 other files it gives its agents.
- AGENTS.mdAGENTS.md
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The file
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 3 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 16
After a batch of customer calls or research sessions
- Distinctive: line 17
When building a case for a feature or pivot
- Distinctive: line 53
If multiple sessions, identify:
- Very specific: line 75
Write findings to memory/feedback/YYYY-MM-DD_[topic].md for future reference.
- Very specific: line 76
Update knowledge/customers/ personas if new information warrants it.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
User Interview Synthesizer
Turn raw interview notes, call transcripts, or usability test observations into structured, reusable insights. Designed for consumer/mobile PMs who talk to users frequently and need to spot patterns fast.
When to Use
- "Synthesize these interview notes"
- "What themes are in these user calls?"
- "Process my research notes"
- "Summarize this usability test"
- After a batch of customer calls or research sessions
- When building a case for a feature or pivot
Process
1. Ingest the Raw Input
Accept notes in any format — bullet points, transcripts, pasted call notes, voice memo transcriptions. Ask:
- How many sessions? (1 interview or a batch)
- Who were the participants? (persona, segment, new vs. power user)
- What were you trying to learn? (the research question)
2. Extract Per-Session
For each interview/session, pull out:
Quotes — verbatim user language (these are gold for stakeholder buy-in)
- Flag emotional language ("I hate when...", "I wish...", "I love that...")
- Note workarounds users have built (signals unmet need)
Pain Points — problems the user described or demonstrated
- Severity: blocks a task vs. annoying vs. cosmetic
- Frequency: every time vs. sometimes vs. once
Goals & Motivations — what the user is ultimately trying to accomplish
- Functional goals (get X done)
- Emotional goals (feel confident, feel in control)
- Social goals (look good to others, share with friends)
Behaviors — what the user actually does (vs. what they say they do)
- Current workflow and tools
- Hacks, workarounds, alternative products used
Surprises — anything that challenged your assumptions
3. Cross-Session Synthesis
If multiple sessions, identify:
Themes — patterns that appear across 2+ sessions
- Rank by frequency (how many users mentioned it)
- Note convergence vs. divergence across segments
Jobs to Be Done — cluster findings into JTBD format
- "When I [situation], I want to [motivation], so I can [outcome]"
- Reference
knowledge/customers/for existing persona alignment
Opportunity Areas — gaps between user goals and current product
- Map to existing roadmap items if applicable (
knowledge/products/*/roadmap.md)
4. Assess Confidence
For each theme or insight:
- Strong signal — 3+ users, consistent, unprompted
- Emerging signal — 2 users, or prompted but consistent
- Weak signal — 1 user, or contradicted by others
5. Store Insights
Write findings to memory/feedback/YYYY-MM-DD_[topic].md for future reference.
Update knowledge/customers/ personas if new information warrants it.
Output
## Research Synthesis: [Topic]
**Date:** YYYY-MM-DD
**Sessions:** [count]
**Participants:** [persona/segment breakdown]
**Research question:** [what we wanted to learn]
### Top Themes
| # | Theme | Frequency | Confidence | Key Quote |
|---|-------|-----------|------------|-----------|
| 1 | [theme] | [X of Y users] | Strong/Emerging/Weak | "[quote]" |
### Pain Points
| Pain Point | Severity | Frequency | Segment |
|------------|----------|-----------|---------|
| [pain] | High/Med/Low | [X of Y] | [segment] |
### Jobs to Be Done
- When I [situation], I want to [motivation], so I can [outcome]
### Opportunity Areas
| Opportunity | Roadmap Link | User Evidence |
|-------------|-------------|---------------|
| [opportunity] | [existing item or "new"] | [summary] |
### Surprises & Assumptions Challenged
- [surprise]
### Recommended Next Steps
- [action: more research / build experiment / write PRD / update roadmap]Principles
- Verbatim quotes > your interpretation — capture their words
- Behaviors > opinions — what they do matters more than what they say
- Patterns > anecdotes — one user's rant isn't a trend
- Connect to roadmap — insights are useless if they don't influence decisions
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Your trail
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Now do this for your own.
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