Persona Development

SkillDev tools

Create and maintain user personas from research data for product targeting

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Persona Development skill

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/product-management/skills/persona-development/SKILL.md and read by ahel’s review.

Overview

Specialized skill for creating and maintaining user personas from research data. Enables product teams to develop rich, data-driven personas that guide product decisions and marketing strategies.

Capabilities

Persona Creation

  • Generate persona profiles from research data
  • Identify persona segments from analytics data
  • Create jobs-to-be-done per persona
  • Synthesize interview data into persona attributes
  • Define demographic and psychographic profiles

Persona Management

  • Update personas with new research findings
  • Version and track persona evolution
  • Validate personas against behavioral data
  • Identify emerging persona segments
  • Retire outdated personas

Persona Application

  • Map personas to product features
  • Calculate persona TAM/SAM estimates
  • Generate persona comparison matrices
  • Create persona-based user journeys
  • Prioritize features by persona impact

Target Processes

This skill integrates with the following processes:

  • user-story-mapping.js - Persona-driven story mapping
  • jtbd-analysis.js - Jobs per persona analysis
  • feature-definition-prd.js - Persona targeting in PRDs
  • product-launch-gtm.js - Persona-based launch targeting

Input Schema

{
  "type": "object",
  "properties": {
    "mode": {
      "type": "string",
      "enum": ["create", "update", "analyze", "map"],
      "description": "Operation mode"
    },
    "researchData": {
      "type": "object",
      "properties": {
        "interviews": { "type": "array", "items": { "type": "object" } },
        "surveys": { "type": "array", "items": { "type": "object" } },
        "analytics": { "type": "object" },
        "supportTickets": { "type": "array", "items": { "type": "object" } }
      },
      "description": "Research data sources for persona creation"
    },
    "existingPersonas": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "id": { "type": "string" },
          "name": { "type": "string" },
          "description": { "type": "string" },
          "attributes": { "type": "object" }
        }
      }
    },
    "segmentationCriteria": {
      "type": "array",
      "items": { "type": "string" },
      "description": "Criteria for persona segmentation"
    },
    "productFeatures": {
      "type": "array",
      "items": { "type": "string" },
      "description": "Features to map to personas"
    }
  },
  "required": ["mode"]
}

Output Schema

{
  "type": "object",
  "properties": {
    "personas": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "id": { "type": "string" },
          "name": { "type": "string" },
          "tagline": { "type": "string" },
          "demographics": {
            "type": "object",
            "properties": {
              "role": { "type": "string" },
              "industry": { "type": "string" },
              "companySize": { "type": "string" },
              "experience": { "type": "string" }
            }
          },
          "psychographics": {
            "type": "object",
            "properties": {
              "goals": { "type": "array", "items": { "type": "string" } },
              "frustrations": { "type": "array", "items": { "type": "string" } },
              "motivations": { "type": "array", "items": { "type": "string" } },
              "behaviors": { "type": "array", "items": { "type": "string" } }
            }
          },
          "jobs": {
            "type": "array",
            "items": {
              "type": "object",
              "properties": {
                "job": { "type": "string" },
                "importance": { "type": "string" },
                "currentSolution": { "type": "string" }
              }
            }
          },
          "quotes": { "type": "array", "items": { "type": "string" } },
          "marketSize": {
            "type": "object",
            "properties": {
              "tam": { "type": "string" },
              "sam": { "type": "string" },
              "som": { "type": "string" }
            }
          }
        }
      }
    },
    "featureMapping": {
      "type": "object",
      "description": "Mapping of features to personas with priority"
    },
    "comparisonMatrix": {
      "type": "object",
      "description": "Comparison of personas across key dimensions"
    },
    "recommendations": {
      "type": "array",
      "items": { "type": "string" }
    }
  }
}

Usage Example

const personas = await executeSkill('persona-development', {
  mode: 'create',
  researchData: {
    interviews: [
      { id: 'int-1', role: 'Product Manager', painPoints: ['...'], goals: ['...'] },
      { id: 'int-2', role: 'Developer', painPoints: ['...'], goals: ['...'] }
    ],
    analytics: {
      userSegments: ['enterprise', 'smb', 'startup'],
      behaviorPatterns: ['power-user', 'casual', 'admin']
    }
  },
  segmentationCriteria: ['role', 'company_size', 'use_case']
});

Dependencies

  • Research data formats
  • Segmentation algorithms

Signals

GitHub stars
2k
Forks
112
Last commit
Sep 2026
Advanced
Item type
skill
Key
persona-development
Source
github.com/a5c-ai/babysitter