| name | ux-researcher-designer |
| description | UX research and design toolkit: data-driven persona generation, journey mapping, usability testing frameworks, and research synthesis. Use when creating personas, mapping user journeys, planning usability tests, or synthesizing research findings. Triggers: 'create persona', 'map user journey', 'plan usability test', 'synthesize research'. Do NOT use for UI implementation, visual design, or coding tasks. |
| allowed-tools | ["Bash","Read"] |
UX Researcher & Designer
Generate research-backed UX artifacts from user data.
Core Capabilities
- Persona generation: Analyze behavior patterns, identify archetypes, extract psychographics, generate scenarios, score confidence by sample size.
- Journey mapping: Map customer touchpoints, identify pain points, surface opportunities.
- Usability testing: Create test frameworks, define tasks, structure findings.
- Research synthesis: Aggregate insights across studies, prioritize by impact.
Persona Generator
Run: python scripts/persona_generator.py [json]
Input: JSON with user behavior data and interview transcripts.
Output: Research-backed personas with design implications.
Required Input Fields
users: Array of user behavior records (sessions, actions, demographics).interviews (optional): Array of interview transcript summaries.
Output Includes
- Persona archetype with name, demographics, goals, frustrations.
- Behavioral patterns and psychographic profile.
- Usage scenarios with design implications.
- Confidence score based on sample size (
low < 10, medium 10-50, high > 50).
Error Handling
- If input JSON is malformed, report the parse error with the expected schema.
- If sample size is below 5, warn that personas are speculative and flag confidence as
very low.
- If no interview data is provided, note that psychographic depth is limited to behavioral inference only.
