Menu

Individual skill

synthetic-user-research

0upvotes

Use AI personas for early-stage research signal — with hard guardrails on what synthetic methods can and cannot validate. Use when asked to run synthetic user testing, simulate user reactions with AI personas, pretest a survey or message before fielding it, or decide whether synthetic research is appropriate at all. Produces a fit verdict for the question at hand, a persona-panel design grounded in real data, the findings labelled as synthetic throughout, and the follow-up plan with real humans. Never a substitute for discovery interviews — see discovery-interview-guide and user-research-synthesis for the real thing.

plugins/pm-research/skills/synthetic-user-research/SKILL.md

Read pinned source

Source commit e0009a385c480fb0b5687e7412df67c7c64f7cee

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
No
Repository scan complete
No
Skill scan complete
No
Observed behavior
Not checked yet
Last checked
Nov 12, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
1,542
Repository last updated
Nov 11, 2026
License
MIT

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

# Synthetic User Research Skill

AI personas are the most misused research tool of the decade — and genuinely useful inside a narrow lane. The difference is the question you ask them. Synthetic panels can catch comprehension failures, confusing flows, and survey defects *before you spend real participants on them*; they cannot tell you what people will pay for, feel, or do. This skill enforces the lane, then runs the method properly.

## What This Skill Produces

- A **fit verdict**: is this question answerable synthetically at all? (Sometimes the deliverable is "no — here's the human study instead")
- A **persona-panel design** grounded in real data you already have, with provenance per persona
- **Findings, labelled synthetic throughout**, with confidence calibrated to the method's floor
- The **human follow-up plan** — what the synthetic pass earned you the right to test properly

## The Lane (checked before anything runs)

**Synthetic methods CAN usefully probe** — because the answer lives in the artifact, not in human hearts:
Back to top