recipes

Create, validate, and debug Goose recipes using YAML configuration.

1|Updated Sep 17, 2025

Search Tags:#validation #configuration #ai agent #yaml #goose #recipe

Ready to run

npx skills add https://github.com/mpazaryna/agentic-factory --skill recipes-mpazaryna

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: recipes
Source: https://github.com/mpazaryna/agentic-factory/tree/main/platform/goose/skills/recipes
Command: npx skills add https://github.com/mpazaryna/agentic-factory --skill recipes-mpazaryna

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) and references (resource) components.

What problem does it solve?

This Skill simplifies the creation, validation, and management of Goose recipes, which are reusable AI agent configurations, streamlining AI agent development and deployment.

Core Features & Use Cases

Recipe Creation: Define reusable AI agent configurations with parameters, extensions, retry logic, and structured outputs.
Validation: Ensure recipe files adhere to the required structure and syntax.
Debugging: Troubleshoot common issues encountered during recipe development.
Use Case: You need to create a standardized AI agent configuration for sentiment analysis that can be easily shared and reused across multiple projects. This Skill helps you define and validate that recipe.

Quick Start

Create a new recipe file using the basic-recipe-template.yaml as a starting point.

Frequently Asked Questions about recipes

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

FAQPage Schema

How do I create and validate Goose AI agent configurations in YAML?▼

To create and validate Goose AI agent configurations, define reusable recipes in YAML that specify parameters, extensions, retry logic, and structured outputs. This ensures deterministic AI agent setups by adhering to the required syntax and structure.

What are Goose recipes used for in AI agent development?▼

Goose recipes are reusable AI agent configurations used to standardize and streamline AI agent development. They simplify deployment by allowing you to define parameters and structured outputs for deterministic setups that can be shared across multiple projects.

How do I debug issues with my Goose recipe configuration file?▼

To debug Goose recipe configuration issues, troubleshoot common YAML syntax errors or structural deviations. Validate your recipe files against the required structure to ensure parameters, extensions, and retry logic are correctly defined.

Are there templates available for common Goose recipe use cases like file processing?▼

Yes, templates are available for common Goose recipe use cases like MCP server access and file processing. You can start from a basic-recipe-template.yaml file to quickly define and structure your reusable AI agent configurations.

What is the best way to structure a reusable AI agent configuration for sentiment analysis?▼

The best way to structure a reusable AI agent configuration is to use a YAML recipe template. Define your parameters, extensions, and structured outputs to create a standardized setup that can be shared and reused across multiple projects.

Do I need specific extensions to access an MCP server with my Goose recipe?▼

Yes, accessing an MCP server requires defining the appropriate extensions within your Goose recipe. By configuring these extensions in your YAML file, you enable the AI agent to interact with the server during file processing or other tasks.