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User Personas Agent Skill

byphuryn26KGitHub starsGitHub

Turn survey data, interviews, or CSVs into 3 refined user personas with jobs-to-be-done, pain points, gains, and unexpected insights. Start free.

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Full Demo

See behavioral personas with JTBD, pains, quotes, unexpected insights, and product decisions.

Get started

Run Your First Task

  1. the step of user personas agent skill
    01

    Install

    Add the User Personas Skill to your AI agent.

  2. the step of user personas agent skill
    02

    Upload Your Research Data

    Provide interviews, surveys, or CSV files.

  3. the step of user personas agent skill
    03

    Get Your Personas

    Receive an HTML report with 3 personas, JTBD, quotes, and unexpected insights.

Install command

$ npx skills add https://github.com/phuryn/pm-skills/tree/main/pm-market-research/skills/user-personas

Installation signals

Installation activity

About

Create refined user personas from research data with this product research skill. It helps product managers, researchers, and founders turn raw survey responses, interview transcripts, or CSVs into three actionable personas that surface jobs-to-be-done, pain points, desired gains, and unexpected insights.

Unlike basic persona templates, this skill follows a structured research synthesis process: data collection, pattern recognition, segmentation, enrichment, and validation. Each persona output includes age range, role, primary job-to-be-done, top 3 pain points, top 3 desired gains, one unexpected behavioral insight, and a product fit assessment for your product.

Use it to segment users for roadmap decisions, synthesize JTBD interviews, or validate product-market fit before development. Because all insights are grounded in your research data, the personas remain distinct, non-overlapping, and actionable for product and marketing teams.

Key features

What makes it powerful

  • Generate 3 refined user personas

    Analyze CSV, Excel, survey responses, or interview transcripts and synthesize three distinct, data-grounded personas.

  • Capture jobs-to-be-done

    Define the core outcome each persona is trying to achieve, including context and frequency of the job.

  • Map pains and desired gains

    Identify top 3 pain points and top 3 desired gains per persona, showing impact and success metrics.

  • Surface unexpected behavioral insights

    Uncover counterintuitive patterns from research data that reveal what motivates users beyond demographics.

  • Assess product fit

    Evaluate how your product or feature meets each persona's needs and flag friction points or unmet needs.

Use cases

When to reach for it

  • Segment users for product decisions

    Group survey or interview respondents into distinct user personas to focus roadmap and feature prioritization.

  • Build personas from research data

    Feed CSV, Excel, or interview transcripts into the skill and get actionable profiles for product teams.

  • Guide JTBD research synthesis

    Turn jobs-to-be-done interviews into persona profiles that highlight desired outcomes and obstacles.

  • Validate product-market fit

    Use product fit assessments per persona to spot unmet needs and reduce risk before development.

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

  • User Interviews: The Ultimate Guide to Research Interviews
  • Market Research: Advanced Techniques
  • Jobs-to-be-Done Masterclass with Tony Ulwick and Sabeen Sattar (video course)

FAQ