What verticals does the Recommendations skill support?

The skill currently supports five primary verticals: movies/TV, restaurants, consumer products, travel destinations, and job listings.

Does this skill require an external API key?

Yes, it requires a TasteRay API key passed via the X-API-Key header to communicate with the TasteRay recommendation engine.

How does this skill differ from basic recommendation APIs?

It follows the principle that 'understanding precedes recommendation,' building deep psychological and contextual profiles from user conversations before querying the API.

Can I use this for E-commerce applications?

Absolutely. The product vertical is specifically designed to handle price constraints, brand affinities, and feature priorities for retail use cases.

How does the skill handle low-confidence matches?

It interprets confidence scores from the API and adjusts its presentation, either omitting weak matches or providing clear caveats explaining why a match might be imperfect.

TasteRay Personalized Recommendations

Name: TasteRay Personalized Recommendations
Author: tasteray

bytasteray

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API 개발

Delivers deeply personalized recommendations across multiple verticals by integrating TasteRay's psychological profiling API into the Claude Code workflow.

This skill empowers Claude to provide highly relevant suggestions for movies, restaurants, travel, products, and jobs by leveraging the TasteRay API. Unlike standard recommendation engines, it prioritizes deep user understanding, building rich context from conversational history and psychological profiles before querying. It features sophisticated confidence scoring, automated context extraction of preferences and constraints, and personalized explanation logic to ensure every recommendation feels tailored and authentic to the user's unique personality and taste profile.

주요 기능

01Integration with psychological profiling for high-resonance matching

028 GitHub stars

03Automated context building from natural language conversations

04Confidence-based presentation logic with personalized explanations

05Multi-vertical support for movies, dining, travel, products, and jobs

06Iterative refinement based on real-time user feedback and critiques

사용 사례

01Integrating personalized product matching into an AI-driven e-commerce assistant

02Enhancing a digital concierge with precise local restaurant and travel recommendations

03Developing a discovery application that suggests content based on deep psychological profiles

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add tasteray/skills recommendations

For use in Claude.ai and ChatGPT

Download Skill