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ianklassenianklassen/ai-pm-system/skills/user-interview-synth/SKILL.md

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.

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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
  1. Distinctive:

    After a batch of customer calls or research sessions

    line 16
  2. Distinctive:

    When building a case for a feature or pivot

    line 17
  3. Distinctive:

    If multiple sessions, identify:

    line 53
  4. Very specific:

    Write findings to memory/feedback/YYYY-MM-DD_[topic].md for future reference.

    line 75
  5. Very specific:

    Update knowledge/customers/ personas if new information warrants it.

    line 76

≈ “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.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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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