User Interview SynthesisCAUTION

1255 professional Agent Skills for Claude, ChatGPT, Gemini, Cursor & Codex — PRDs, postmortems, leases, medical bills, layoffs, go-bags, new countries. Plain markdown, MIT, in Anthropic's plugin directory. Plus a typed decision layer: which skill, is it safe, ship or slip. Free in-browser or npx pm-

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: user-interview-synthesis
description: "Synthesises user interview transcripts into structured research findings. Use when asked to analyse interview notes, synthesise qualitative research, identify themes from interviews, or turn raw interview data into actionable product insights. Produces a themed synthesis with supporting quotes per theme, 'so what' implications, and recommended next steps. For mixed sources beyond interviews (surveys, tickets, feedback) use user-research-synthesis instead."
---

# User Interview Synthesis Skill

Transform raw interview transcripts into a structured synthesis document that surfaces themes, pain points, and actionable insights.

## Required Inputs

Work from what is given. If any of these is missing, still produce the complete output: fill each gap with a reasonable assumption marked *(assumed, confirm)* and list those assumptions at the end. Ask a question first only when the core subject itself is missing (there is nothing to write about).
- **Interview transcripts or notes** (even rough notes work)
- **Number of participants and their profiles** (role, company size, context)
- **Research questions** (what was the study trying to answer?)
- **Date range** of research (for context)

## Process
1. Read all provided transcripts fully before drawing conclusions
2. Identify recurring themes (minimum 3 mentions to qualify as a theme)
3. Categorize findings into: Pain Points, Workflow Insights, Feature Requests, Delight Moments
4. Select 2-3 verbatim quotes per theme that best represent the pattern
5. Draft "So What" implications for each theme — what does this mean for the product?
6. **Validate** — Confirm every theme has quotes from at least 3 participants. Flag any insight resting on fewer as low-confidence.

## Output Structure

### Research Synthesis: [Study Name]
**Participants:** [n]
**Date Range:** [dates]
**Research Questions:** [list]

#### Theme 1: [Theme Name]
- Summary (2-3 sentences)
- Supporting quotes (from at least 3 participants)
- Implication for product

[Repeat for each theme]

#### Low-Confidence Signals (1-2 participants only)
[Findings worth tracking but not acting on yet — note what further research would confirm or deny]

#### Recommended Next Steps
[Specific, actionable recommendations based on findings]

## Deeper Materials

This skill ships with support files — use them when they are available:

- **`references/coding-transcripts.md`** — Coding Interview Transcripts Without Losing the Signal. Apply it while producing the output; it carries the calibration and judgment calls the method summary above compresses.
- **`templates/per-session-capture.md`** — a fill-in version of the deliverable with the quality gates inline. Offer it when the user wants to work the document themselves rather than have it generated.

## Scoring Rubric (0–40)

Score any output of this skill before handing it over; 32+ is ship-quality.

| Dimension | 0 | 5 | 10 |
|---|---|---|---|
| Evidence traceability | Themes asserted with no quotes or participant attribution | Most themes carry quotes, but some rest on 1–2 participants or unattributed paraphrase | Every theme carries verbatim quotes from ≥3 distinct participants, with frequency counts ("6 of 9") consistent with the roster |
| Implication actionability | Implications restate the observation ("users find X frustrating") | Implications gesture at direction but name no decision, owner, or change | Every implication enables a specific product decision someone could act on this quarter |
| Contradiction honesty | All findings conveniently support the sponsor's hypothesis; inconvenient data absent | Contradictory evidence present but buried or softened; both-ways quotes trimmed to the helpful half | Findings that contradict the hypothesis are surfaced prominently, and ambiguous quotes are kept whole with the tension flagged |
| Signal separation & question coverage | Single-source anecdotes mixed into main themes; research questions ignored | Low-confidence signals segregated but with no follow-up path, or one research question left unaddressed | Every 1–2-participant signal sits in its own section with the cheap test that would confirm it, and every research question gets an explicit answer — including "inconclusive" |

## Quality Checks

- [ ] Every theme is supported by quotes from at least 3 participants
- [ ] Implications connect to specific product decisions, not just observations
- [ ] Researcher bias check: no leading language, findings don't all support one hypothesis
- [ ] Single-source signals are flagged separately, not mixed into main themes
- [ ] Research questions from the study brief are each addressed (even if the answer is "inconclusive")

## Anti-Patterns

- [ ] Do not mix single-source signals into main themes — insights cited by only one participant must be flagged separately
- [ ] Do not write implications that are observations restated rather than product decisions enabled
- [ ] Do not include themes that only support the project hypothesis — contradictory findings must be surfaced, not omitted
- [ ] Do not present findings without quotes — every theme requires verbatim evidence from at least 3 participants
- [ ] Do not leave research questions unanswered — each question from the study brief must be explicitly addressed, even if the answer is inconclusive

## Example Trigger Phrases

- "Analyse interview notes."
- "Synthesise qualitative research."
- "Turn raw interview data into actionable product insights."

CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.

What the source does

Filesystem

none-observed

Network

none-observed

Shell

none-observed

Dependencies

pinned

Secrets in source

none-found

Findings (5)

templates/pm-discovery-agent/skills/assumption-mapper/SKILL.md

templates/pm-discovery-agent/skills/discovery-interview-guide/SKILL.md

templates/pm-discovery-agent/skills/job-story-mapper/SKILL.md

templates/pm-discovery-agent/skills/user-interview-synthesis/SKILL.md

templates/pm-launch-agent/skills/content-calendar/SKILL.md

Gates applied: no_behavioural_pass.