prose

Orchestrate multi-agent AI workflows through a VM-like scripting surface.

Updated Apr 24, 2026
One-click install
npx skills add https://github.com/frankhli843/gemmahermes --skill prose-frankhli843
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: prose
Source: https://github.com/frankhli843/gemmahermes/tree/main/extensions/open-prose/skills/prose
Command: npx skills add https://github.com/frankhli843/gemmahermes --skill prose-frankhli843

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

OpenProse provides a unified framework to orchestrate multi-agent AI workflows, enabling a single command surface to spawn, coordinate, and manage the execution of subagents across backends and runtimes.

Core Features & Use Cases

  • OpenProse VM surface: Define agents, sessions, parallel blocks, loops, blocks, and imports in a single, self-describing language to orchestrate complex workflows.
  • Stateful orchestration: Tracks execution state, context passing, and memory for persistent agents across runs with filesystem or database backends.
  • Extensible planning patterns: Includes support for blocks, pipelines, error handling, and multi-stage orchestration, enabling production-grade automations.
  • Use Case: Build an orchestrated data-processing pipeline that runs multiple agent reviews in parallel and synthesizes a final report.

Quick Start

Create a simple, end-to-end OpenProse workflow by defining a small agent and a session, then run a session to observe binding creation and context propagation.

Frequently Asked Questions about prose

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

FAQPage Schema
How do I orchestrate multi-agent AI workflows with parallel execution and persistent memory?▼

You can orchestrate multi-agent AI workflows by using a VM-like scripting surface to define agents, sessions, parallel execution blocks, and memory management across local backends.

What is a structured VM for coordinating AI agents and how does it work?▼

A structured VM for AI agents provides a self-describing language to define blocks, pipelines, and loops, enabling stateful orchestration and context passing across multiple subagents.

Can I manage stateful orchestration and execution context using filesystem or database backends?▼

Yes, stateful orchestration tracks execution state and context passing using recommended state backends like filesystem, SQLite, or PostgreSQL to support persistent agents across runs.

How do I build a data-processing pipeline that runs multiple agent reviews in parallel?▼

To build a parallel data-processing pipeline, define a small agent and a session using the VM surface, then execute the session to observe binding creation, context propagation, and final report synthesis.

Does this multi-agent orchestration framework support error handling and multi-stage automations?▼

Yes, the framework includes extensible planning patterns that support blocks, pipelines, error handling, and multi-stage orchestration to build robust, reusable, production-grade automations.