TasteRay Skills

Understand user preferences through conversation and apply them to recommendations.

TasteRay’s complete two-Skill package joins conversational elicitation with recommendations. It uses narrative and motivational-interviewing approaches, then connects preferences to supported recommendation categories.

Use cases

• Explore a person’s values and preferences
• Recommend items with reasons
• Personalize a conversational experience

How to use

Begin with a gradual conversation rather than a survey. Preserve the resulting preference context; API-backed recommendations require the TasteRay integration setup described upstream.

Skills

• elicitation

  Psychological profiling through natural conversation using narrative identity research (McAdams), self-defining memory elicitation (Singer), and Motivational Interviewing (OARS framework). Use when you need to: (1) understand someone's core values and motivations, (2) discover formative memories and life-defining experiences, (3) detect emotional schemas and belief patterns, (4) build psychological profiles through gradual disclosure, (5) conduct user interviews that reveal deep insights, (6) design conversational flows for personal discovery, (7) identify identity themes like redemption and contamination narratives, (8) elicit authentic self-disclosure without interrogation.

  tasteray/skills

• recommendations

  TasteRay API integration for personalized recommendations across verticals (movies, restaurants, products, travel, jobs). Use when you need to: (1) recommend movies, restaurants, products, travel, or jobs, (2) answer "what would I like" questions, (3) provide personalized recommendations based on preferences, (4) rank or score items for a user, (5) explain why something matches a user's taste, (6) build recommendation context from conversation, (7) integrate psychological profiles with recommendation systems.

  tasteray/skills