urf

Orchestrate modular holons into scalable multi-domain reasoning workflows.

7|3|Updated Jan 15, 2026
One-click install
npx skills add https://github.com/Zpankz/mcp-skillset --skill urf
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: urf
Source: https://github.com/Zpankz/mcp-skillset/tree/main/urf
Command: npx skills add https://github.com/Zpankz/mcp-skillset --skill urf

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

The URF framework addresses the need for scalable, cross-domain reasoning by coordinating modular holons to perform complex analysis, synthesis, and decision support.

Core Features & Use Cases

  • Hierarchical λο.τ reasoning across micro, meso, and macro scales
  • Pipeline-based routing (R0–R3) for direct answers to full orchestration
  • Multi-modal guidance via knowledge graphs, graph analytics, and governance checks
  • Real-world scenarios include research synthesis, system design, crisis response, and performance optimization

Quick Start

Provide a complex, multi-domain problem and let URF orchestrate reasoning from analysis to action.

Frequently Asked Questions about urf

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

FAQPage Schema
How do I orchestrate multi-domain reasoning for complex system design?

Multi-domain reasoning orchestration coordinates modular holons into scalable workflows, routing analysis through pipelines to synthesize research, manage crises, and optimize performance across micro to macro scales.

What is pipeline routing for cross-domain analysis?

Pipeline routing directs cross-domain analysis complexity from direct answers to full orchestration using R0 to R3 routes, enforcing invariants like η≥4 and KROG constraints to scale modular reasoning.

Can I use knowledge graphs for crisis management and research synthesis?

Knowledge graphs provide multi-modal guidance for crisis management and research synthesis, enabling graph analytics and governance checks within orchestrated workflows to support hierarchical reasoning scales.

Does modular holon orchestration support performance optimization at scale?

Modular holon orchestration supports performance optimization by applying hierarchical reasoning across micro, meso, and macro scales, coordinating scalable workflows that enforce invariants like η≥4 during analysis.

When do I need full orchestration instead of direct reasoning pipelines?

Full orchestration is needed for complex multi-domain tasks requiring research synthesis or crisis management, utilizing R3 pipeline routing to coordinate modular holons when direct reasoning proves insufficient.

What are the limitations of invariant constraints in scalable reasoning workflows?

Invariant constraints like η≥4 and KROG limitations in scalable reasoning workflows enforce strict governance checks, potentially restricting pipeline routing flexibility when handling highly ambiguous multi-domain inputs.