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recipe-generator

Generate personalized recipes using multi-model consensus across Mistral, Llama, and Mixtral.

Updated Dec 22, 2025
Search Tags:#consensus#generation#nutrition#multimodel#recipe#allergies#dietary-preferences
One-click install
npx skills add https://github.com/ayia/NutriProfile --skill recipe-generator-ayia
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: recipe-generator
Source: https://github.com/ayia/NutriProfile/tree/main/.claude/skills/recipe-generator
Command: npx skills add https://github.com/ayia/NutriProfile --skill recipe-generator-ayia

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

NutriProfile users often face inconsistent recipe ideas and manual, time-consuming generation when combining multiple dietary needs and ingredients. This skill coordinates AI agents across Mistral, Llama, and Mixtral to produce coherent, tailored recipes that respect allergies, nutrition goals, and user preferences.

Core Features & Use Cases

  • Multi-model consensus across three AI agents to improve recipe quality and reliability.
  • Incorporates user dietary preferences, allergies, and nutritional goals into generation.
  • Backend and frontend integration with models, API endpoints, and UI components for the Recipes page.
  • Tracks generated recipes with a RecipeHistory model for analytics and personalization.

Quick Start

Provide a list of ingredients and dietary goals to generate a personalized recipe.

Frequently Asked Questions about recipe-generator

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate recipes that respect dietary restrictions and allergies?▼

Recipe generation uses multi-model consensus across Mistral, Llama, and Mixtral to produce tailored recipes that incorporate user dietary preferences, allergies, and nutritional goals into the final output.

What is multi-model consensus for AI recipe generation?▼

Multi-model consensus coordinates AI agents across Mistral, Llama, and Mixtral to validate and synthesize recipe outputs, improving generation quality and reliability when combining ingredients with dietary constraints.

How do I integrate AI recipe generation into a web application backend?▼

AI recipe generation provides API endpoints, a recipe data model, nutrition calculation logic, and frontend integration components for the Recipes page, along with a RecipeHistory model for analytics tracking.

Can I generate recipes based on specific ingredients I already have?▼

Ingredient-driven generation allows you to provide a list of available ingredients and dietary goals to generate personalized recipes that match your nutrition profile and difficulty preferences.

Does multi-model recipe generation work with time and difficulty preferences?▼

Multi-model recipe generation applies user time bounds and difficulty preferences alongside dietary restrictions and nutrition goals to produce recipes suited to specific cooking scenarios.

Why use multi-model consensus instead of a single AI model for recipe creation?▼

Multi-model consensus across three AI agents reduces inconsistent recipe outputs and manual effort by cross-referencing results from Mistral, Llama, and Mixtral, ensuring coherent recipes for complex dietary needs.

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