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.