skill

Create, validate, and orchestrate YAML-based skills in Ralph's ecosystem.

145|21|Updated Jan 2, 2026

Search Tags:#workflow #validation #ai #discovery #orchestration #yaml #skill

Ready to run

npx skills add https://github.com/alfredolopez80/multi-agent-ralph-loop --skill skill-alfredolopez80

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: skill
Source: https://github.com/alfredolopez80/multi-agent-ralph-loop/tree/main/.claude/commands
Command: npx skills add https://github.com/alfredolopez80/multi-agent-ralph-loop --skill skill-alfredolopez80

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

YAML-based skills enable teams to modularize AI workflows by defining, validating, and orchestrating lightweight capabilities in a consistent format.

Core Features & Use Cases

Define skills with a four-file structure: skill.yaml, sharp-edges.yaml, validations.yaml, collaboration.yaml, plus optional directories for scripts, references, and assets.
Validate skill structure, discover skills, and orchestrate cross-skill workflows within Ralph's runtime.
Use cases include creating new capabilities, validating readiness before deployment, listing available skills, and coordinating multi-skill tasks.

Quick Start

Create a new YAML-based skill named my-skill with the four required files.

Frequently Asked Questions about skill

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

FAQPage Schema

How do I create and validate YAML-based skills for AI workflow orchestration?▼

YAML-based skills are created and validated using a required four-file structure: skill.yaml, sharp-edges.yaml, validations.yaml, and collaboration.yaml. This enforces consistent metadata for authoring, validating readiness, and orchestrating cross-skill workflows within Ralph's ecosystem.

What is the required file structure for defining a lightweight YAML skill?▼

The required file structure for a YAML skill includes four files: skill.yaml, sharp-edges.yaml, validations.yaml, and collaboration.yaml. You can also include optional directories for scripts, references, and assets to support the skill's functionality.

How does cross-skill workflow orchestration work with YAML definitions?▼

Cross-skill workflow orchestration coordinates multiple YAML-defined skills during runtime. It uses frontmatter-driven metadata for discovery and leverages the collaboration.yaml file to manage interactions and dependencies between separate modular capabilities.

Can I use frontmatter metadata for AI skill discovery in a YAML workflow?▼

Yes, frontmatter-driven metadata is supported for skill discovery. It allows the runtime to list available skills and identify their capabilities based on the structured metadata defined within the skill.yaml file.

What are the limitations of using a four-file YAML structure for skill management?▼

The four-file YAML structure requires strict adherence to skill.yaml, sharp-edges.yaml, validations.yaml, and collaboration.yaml. This constraint ensures structural validation and deployment readiness but limits skill definitions to this specific architectural format.

Do I need any dependencies to start authoring YAML skills for AI workflows?▼

No dependencies are required to start authoring YAML skills. You can create a new skill by generating the four required YAML files and utilizing optional directories for scripts, references, and assets to modularize your AI workflows.