Agent skill

recipe-persona

Create or update personas with demographic, contextual, JTBD, and behavioral data

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Install this agent skill to your Project

npx add-skill https://github.com/shinpr/claude-code-discover/tree/main/skills/recipe-persona

SKILL.md

Context: Create or update persona files with demographics, context, JTBD, pains/gains, and behavioral patterns. Integrates existing codebase analysis when available.

Orchestrator Definition

Execution Protocol:

  1. Delegate code analysis to codebase-analyzer (via Agent tool, subagent_type: "discover:codebase-analyzer") when existing code reveals user behavior
  2. Follow the persona flow defined below
  3. Stop at every [STOP — BLOCKING] marker — present findings and CANNOT proceed until user explicitly confirms

Workflow Overview

Input (new persona request / persona update / discovery trigger)
    ↓
1. Context Assessment → New vs. Update, existing code?
    ↓
2. Research Gathering → User data, interviews, analytics, code analysis
    ↓
3. Persona Drafting → Using persona-template.md [Stop: User confirms persona]
    ↓
Output: docs/product/personas/persona-[name].md

Execution Decision Flow

1. Context Assessment

Input: $ARGUMENTS

Situation Action
No personas exist Create from scratch — gather user research or assumptions
Personas exist, new data available Update existing personas with new evidence
Existing codebase Invoke codebase-analyzer for real user behavior insights
Post-interview / post-survey Update with new primary research

2. Research Gathering

From Existing Code (if applicable)

Invoke codebase-analyzer using Agent tool (subagent_type: "discover:codebase-analyzer") to identify:

  • User roles and permissions in the system
  • User-facing features and workflows
  • Data models related to users
  • Analytics/tracking events (if present)

From User Research

Gather available data:

  • Interview transcripts or summaries
  • Survey results
  • Support ticket patterns
  • Usage analytics
  • Market research (per business-context skill)

From VPC Analysis

Map Customer Profile from Value Proposition Canvas:

  • Customer jobs (functional, social, emotional)
  • Pains (frustrations, obstacles, risks)
  • Gains (required, expected, desired, unexpected)

3. Persona Drafting

Use design-perspective skill references/persona-template.md to create persona files:

  1. Demographics: Role, experience, technical proficiency, industry
  2. Context: Environment, frequency, time pressure, adjacent tools
  3. JTBD: Primary job, secondary jobs, social/emotional jobs
  4. Pains and Gains: Mapped from research with severity/priority
  5. Behavioral Patterns: Decision-making, adoption tendency, information sources
  6. Validation Status: Based on research quality — mark assumptions explicitly

[STOP — BLOCKING] Present persona draft to user for confirmation:

  • Complete persona draft
  • Evidence sources and confidence level
  • Assumptions that need validation
  • Connections to existing Opportunities (if any)

CANNOT write persona file until user explicitly confirms.

4. File Output

After user approval:

  • Write persona to docs/product/personas/persona-[name].md
  • Update any Opportunity files that reference this persona
  • Update journey maps if persona context changed

Sub-agent Usage

Agent When Why (context separation benefit)
codebase-analyzer Existing codebase with user-facing features Objective analysis of actual user behavior patterns in code

Scope Boundaries

Included: Persona creation, persona update, integration with VPC and code analysis Not included: Journey mapping, user story writing

Completion Criteria

  • Context assessed (create vs. update)
  • Research gathered (code analysis, user data, market research as available)
  • Persona drafted with all template sections
  • Validation status clearly marked (evidence-based vs. assumption)
  • User confirmed persona
  • File written to docs/product/personas/

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