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.

27 starsSoftware Development

Install

skills CLI (Claude Code, Cursor, Codex and more)

npx skills add tasteray/skills --skill recommendations

Manual install

git clone --depth 1 https://github.com/tasteray/skills.git /tmp/skills
mkdir -p ~/.claude/skills
cp -r /tmp/skills/recommendations ~/.claude/skills/recommendations

Personal skills live in ~/.claude/skills. Use .claude/skills in a project folder to share a skill with your team.

From the SKILL.md

# Recommendations

Personalized recommendations through the TasteRay API.

## Goal

When making recommendations or reviewing recommendation-related code—whether API integrations, context building, or presentation logic—**your goal is to achieve a 10/10 score**.

Score all work on a 0-10 scale based on adherence to the principles and techniques in this skill. Provide your assessment as **X/10** with specific feedback on what's working and what needs improvement to reach 10/10.

A 10/10 means the work:
- Embodies the core principle (understanding precedes recommendation)
- Builds rich context before calling the API
- Presents recommendations with personalized explanations
- Handles edge cases gracefully (low confidence, rate limits, errors)
- Avoids all anti-patterns

Iterate until you reach 10/10.

---

## Core Principle

**Understanding precedes recommendation.**

Great recommendations come from deep understanding of the person—their preferences, constraints, history, and context. Never call the API without first building meaningful context from the conversation.

Key insight: A recommendation is only as good as the context that informed it.

---

## API Overview

The TasteRay Recommendation API provides personalized recommendations across multiple verticals.

### Base URL

```
https://api.tasteray.com
```

### Authentication

All requests require an API key in the header:

```
X-API-Key: your-api-key
```

### Core Endpoints

| Endpoint | Method | Description |

Read the full skill on GitHub

Details

Skill name: recommendations
Repository: tasteray/skills
Path: recommendations/SKILL.md
License: MIT
Repo updated: 15 July 2026
Listed in: BehiSecc/awesome-claude-skills

FAQ

What does the Recommendations skill do?

How do I install the Recommendations skill?

skills CLI (Claude Code, Cursor, Codex and more): npx skills add tasteray/skills --skill recommendations. Skills go in ~/.claude/skills (personal) or .claude/skills (project), and Claude loads them automatically when a task matches the description.

Is Recommendations popular?

It lives in tasteray/skills, which has 27 GitHub stars and 0 forks, and is included in 1 curated skill list.

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