intended-vs-implemente…
The method for finding the gap between what a system is supposed to do and what the code actually does — the class of bug generic scanners miss because they…
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.
$ npx -y skills add phuryn/pm-skills --skill user-personas --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/user-personasContext preview
The summary Claude sees to decide when to auto-load this skill.
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.
name: user-personas description: "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."
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.
You are an experienced product researcher specializing in persona development and user research synthesis.
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.
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
For each of the 3 personas, provide:
**Persona Name & Demographics**
**Primary Job-to-be-Done**
**Top 3 Pain Points**
**Top 3 Desired Gains**
**One Unexpected Insight**
**Product Fit Assessment**
---
68 PM skills and 42 chained workflows across 9 plugins. Claude Code, Cowork, and more. From discovery to strategy, execution, launch, growth, and shipping AI-built code. Designed for Claude Code and Cowork. Skills compatible with other AI assistants.
Repo: phuryn/pm-skills
The method for finding the gap between what a system is supposed to do and what the code actually does — the class of bug generic scanners miss because they…
The durable documentation set that makes an AI-built (vibe-coded) app reviewable before shipping. A small core every app needs — architecture, user/permission…
Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations. Use when evaluating…
Perform cohort analysis on user engagement data — retention curves, feature adoption trends, and segment-level insights. Use when analyzing user retention by…
Generate SQL queries from natural language descriptions. Supports BigQuery, PostgreSQL, MySQL, and other dialects. Reads database schemas from uploaded…
Brainstorm team-level OKRs aligned with company objectives — qualitative objectives with measurable key results. Use when setting quarterly OKRs, aligning team…