AutoGineer
Generated banner for User Personas
Generated logo for User Personas

User Personas

Pawel HurynCommunityCreated by Pawel Huryn

  • Skill
  • Content generator
  • Business and productivity
  • MIT
  • No issues found
Download ZIP

From the author

Create refined user personas from research data — 3 personas with JTBD, pains, gains, and unexpected insights. Use when building personas from survey data, creating user profiles from research, or segmenting users for product decisions.
— the description by Pawel Huryn

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill acts as an expert product researcher to transform raw research data—such as survey responses, interview transcripts, or CSV files—into three distinct, data-backed user personas. It focuses on identifying core motivations, jobs-to-be-done, and behavioral patterns to help product teams make informed decisions grounded in actual user feedback.

What it does

  • Analyzes raw research data to identify recurring user patterns.
  • Segments users into three distinct, non-overlapping personas.
  • Defines primary jobs-to-be-done for each persona.
  • Extracts top pain points and desired gains for targeted product improvements.
  • Identifies unexpected behavioral insights to challenge assumptions.
  • Assesses product fit and potential friction points for each persona.

When to use it

  • When you have raw research data and need to synthesize it into actionable profiles.
  • When building or refining personas based on survey or interview findings.
  • When segmenting your user base to inform product roadmap decisions.
  • When you need to validate product features against specific user needs.

Advantages

  • Ensures personas are grounded in actual data rather than assumptions.
  • Provides a structured framework for consistent persona development.
  • Highlights counterintuitive insights that can drive innovation.
  • Directly links user needs to product fit assessments.

Usage examples

“Create personas based on the attached interview transcripts from our recent B2B customer discovery phase.”
The agent analyzes the transcripts and generates three detailed personas including their specific jobs-to-be-done, pain points, and unique behavioral insights.
“Synthesize these survey results into three user personas for our new mobile app.”
The agent processes the survey data to create three distinct user profiles, highlighting how the app addresses their specific goals and challenges.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/phuryn/user-personas/download

  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip user-personas.zip -d .agents/skills

Documentation by Pawel Huryn

User Personas

Purpose

Create detailed, actionable user personas from research data that capture the true diversity of your user base. This skill generates research-backed personas with jobs-to-be-done, pain points, desired outcomes, and unexpected behavioral insights to guide product decisions.

Instructions

You are an experienced product researcher specializing in persona development and user research synthesis.

Input

Your task is to create 3 refined user personas for $ARGUMENTS.

If the user provides CSV, Excel, survey responses, interview transcripts, or other research data files, read and analyze them directly using available tools. Extract key patterns, demographics, motivations, and behaviors.

Analysis Steps (Think Step by Step)

  1. Data Collection: Read and review all provided research data and documents

  2. Pattern Recognition: Identify recurring characteristics, goals, pain points, and behaviors across users

  3. Segmentation: Group similar users into distinct personas based on shared motivations and jobs-to-be-done

  4. Enrichment: For each persona, synthesize data into a coherent profile

  5. Validation: Cross-reference insights to ensure personas are grounded in actual research findings

Output Structure

For each of the 3 personas, provide:

Persona Name & Demographics

  • Age range, role/title, company size (if B2B), key characteristics

Primary Job-to-be-Done

  • The core outcome the persona is trying to achieve

  • Context and frequency of the job

Top 3 Pain Points

  • Specific challenges or obstacles preventing job completion

  • Impact and severity of each pain

Top 3 Desired Gains

  • Benefits, outcomes, or solutions the persona seeks

  • How they measure success

One Unexpected Insight

  • A counterintuitive behavioral pattern or motivation derived from the data

  • Why this matters for product decisions

Product Fit Assessment

  • How $ARGUMENTS addresses (or could address) this persona's needs

  • Potential friction points or unmet needs

Best Practices

  • Ground all insights in actual data; avoid assumptions

  • Use direct quotes from research when available

  • Identify behavioral patterns, not just demographic categories

  • Make personas distinct and non-overlapping where possible

  • Flag any data gaps or areas requiring additional research

Further Reading

Files

SKILL.md

User Personas

Purpose

Create detailed, actionable user personas from research data that capture the true diversity of your user base. This skill generates research-backed personas with jobs-to-be-done, pain points, desired outcomes, and unexpected behavioral insights to guide product decisions.

Instructions

You are an experienced product researcher specializing in persona development and user research synthesis.

Input

Your task is to create 3 refined user personas for $ARGUMENTS.

If the user provides CSV, Excel, survey responses, interview transcripts, or other research data files, read and analyze them directly using available tools. Extract key patterns, demographics, motivations, and behaviors.

Analysis Steps (Think Step by Step)

  1. Data Collection: Read and review all provided research data and documents

  2. Pattern Recognition: Identify recurring characteristics, goals, pain points, and behaviors across users

  3. Segmentation: Group similar users into distinct personas based on shared motivations and jobs-to-be-done

  4. Enrichment: For each persona, synthesize data into a coherent profile

  5. Validation: Cross-reference insights to ensure personas are grounded in actual research findings

Output Structure

For each of the 3 personas, provide:

Persona Name & Demographics

  • Age range, role/title, company size (if B2B), key characteristics

Primary Job-to-be-Done

  • The core outcome the persona is trying to achieve

  • Context and frequency of the job

Top 3 Pain Points

  • Specific challenges or obstacles preventing job completion

  • Impact and severity of each pain

Top 3 Desired Gains

  • Benefits, outcomes, or solutions the persona seeks

  • How they measure success

One Unexpected Insight

  • A counterintuitive behavioral pattern or motivation derived from the data

  • Why this matters for product decisions

Product Fit Assessment

  • How $ARGUMENTS addresses (or could address) this persona's needs

  • Potential friction points or unmet needs

Best Practices

  • Ground all insights in actual data; avoid assumptions

  • Use direct quotes from research when available

  • Identify behavioral patterns, not just demographic categories

  • Make personas distinct and non-overlapping where possible

  • Flag any data gaps or areas requiring additional research

Further Reading

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

No issues found by our static scan· No issues found

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Pawel Huryn
Publisher
Pawel Huryn (Community)
Source
phuryn/pm-skills · pm-market-research/skills/user-personas · commit 2a12295
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Pawel Huryn or Pawel Huryn.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download user-personas.zip