orpheus

Generate and execute multi-skill orchestrated systems from natural language descriptions.

33|2|Updated Apr 15, 2026
One-click install
npx skills add https://github.com/nuryslyrt/ORPHEUS --skill orpheus
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: orpheus
Source: https://github.com/nuryslyrt/ORPHEUS/tree/main/skill
Command: npx skills add https://github.com/nuryslyrt/ORPHEUS --skill orpheus

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pyyaml, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Building multi-agent AI systems traditionally requires managing N separate LLM instances, inter-agent communication protocols, state management, deployment infrastructure, and glue code. ORPHEUS eliminates this complexity by structuring existing coding agent capabilities into composable skills, requiring no additional infrastructure.

Core Features & Use Cases

  • Multi-Skill Orchestration: Decompose natural language requests into coordinated expert and worker skills with automatic dependency management and parallel execution.
  • Zero-Infrastructure Execution: Runs entirely on the coding agent's native capabilities—tool access, subagent spawning, and filesystem I/O—no Docker, services, or Python glue code required.
  • Provable Assurance: Built-in auditing and validation with evidence packages for deployment approval decisions, including claim matrices and renewal triggers.
  • Use Case: A user describes "Build a content pipeline that researches topics, writes articles, reviews for accuracy, and publishes to my blog" and ORPHEUS generates a complete validated system with 4 experts, 5 workers, and a 4-stage sequential pipeline in 30 seconds.

Quick Start

Use the orpheus skill to build a new multi-skill pipeline by describing the automated workflow you want to create in plain language.

Frequently Asked Questions about orpheus

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

FAQPage Schema
What is declarative pipeline generation from natural language descriptions?

You can build multi-skill pipelines by describing your automated workflow in natural language, which generates a declarative pipeline with automatic dependency management and parallel execution using the coding agent's native filesystem I/O.

Do I need Docker or external services to run multi-agent AI systems?

Workflow orchestration is automated by decomposing natural language requests into coordinated expert and worker skills with automatic dependency management, enabling parallel execution and contract-based composition without requiring Python glue code.

How does assurance auditing work for automated pipeline validation?

You do not need Docker or external services to run multi-agent AI systems. Execution relies entirely on the coding agent's native capabilities, including subagent spawning and filesystem I/O, for self-contained operation.

Can I use pyyaml for dependency management in orchestrated systems?

Assurance auditing validates automated pipelines by generating built-in evidence packages for deployment approval decisions, including claim matrices and renewal triggers to ensure provable system correctness.

What are the limitations of filesystem-based state management for workflow automation?

You can use pyyaml as the required dependency for orchestrated systems, supporting declarative pipeline generation and contract-based composition while managing coordinated expert and worker skill dependencies.

What is multi-skill orchestration for workflow automation?

Multi-skill orchestration is the process of decomposing natural language requests into coordinated expert and worker skills with automatic dependency management and parallel execution for workflow automation.