prose

Orchestrate AI workflows with a VM managing sessions and parallel blocks.

Updated Aug 31, 2024
One-click install
npx skills add https://github.com/iheCoder/Lib --skill prose-ihecoder
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: prose
Source: https://github.com/iheCoder/Lib/tree/main/skill/open-prose/skills/prose
Command: npx skills add https://github.com/iheCoder/Lib --skill prose-ihecoder

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

OpenProse provides a VM-driven framework to orchestrate AI agents, enabling complex, multi-step workflows with deterministic execution order, persistent state, and reusable components.

Core Features & Use Cases

  • Orchestrates multiple agents and tasks within a single program, including parallel, blocks, and imports.
  • Supports state persistence and various backends (filesystem, in-context, SQLite, PostgreSQL) for long-running workflows and collaboration.
  • Ideal for captain’s chair patterns, production pipelines, and research automations across teams.

Quick Start

Start by loading prose.md and running a small .prose example to observe how the VM orchestrates sessions and returns binding pointers.

Frequently Asked Questions about prose

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

FAQPage Schema
How do I orchestrate parallel AI agent workflows with persistent state?

You orchestrate parallel AI agent workflows with persistent state by using a VM that spawns sessions, coordinates parallel blocks, and tracks state across runs. This enables deterministic execution order for complex, multi-step automations.

What is the best way to coordinate multi-agent AI pipelines for production environments?

The best way to coordinate multi-agent AI pipelines for production environments is using a VM-driven framework. It orchestrates multiple agents within a single program, ensuring deterministic execution order, persistent state, and reusable components.

Can I use persistent state backends like SQLite or PostgreSQL for long-running AI automations?

Yes, you can use persistent state backends like SQLite or PostgreSQL for long-running AI automations. The framework supports filesystem, in-context, SQLite, and PostgreSQL backends to track state across runs and facilitate collaboration.

How do I start running a program to observe AI workflow orchestration and session spawning?

To start running a program and observe AI workflow orchestration, load the core documents and execute a small example program. The VM will orchestrate sessions and return binding pointers to demonstrate the workflow logic.

Does this AI workflow orchestration framework support reusable components and imports?

Yes, this AI workflow orchestration framework supports reusable components and imports. It orchestrates multiple agents and tasks within a single program, allowing you to import components and structure workflows using parallel blocks.

When do I need a VM-driven framework for AI workflow orchestration instead of standard scripts?

You need a VM-driven framework for AI workflow orchestration when building repeatable AI pipelines, multi-agent orgs, or production-grade automations. It provides deterministic execution order, persistent state, and reusable components that standard scripts lack.