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frames-engineeringOFFICIAL
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open-prose

Define and execute multi-agent workflows with structured syntax.

4|2|Updated Feb 3, 2026
Search Tags:#workflow automation#prose#ai orchestration#declarative programming#agent programming#llm operations
One-click install
npx skills add https://github.com/frames-engineering/skills --skill open-prose-frames-engineering
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: open-prose
Source: https://github.com/frames-engineering/skills/tree/main/skills/open-prose
Command: npx skills add https://github.com/frames-engineering/skills --skill open-prose-frames-engineering

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) and common (resource) and lib (resource) and guidance (resource) and alts (resource) and examples (resource) components.

What problem does it solve?

This Skill automates the creation and execution of complex AI workflows by providing a structured programming language for AI sessions, eliminating the need for manual prompt chaining and context management.

Core Features & Use Cases

  • AI Workflow Orchestration: Define multi-agent systems, parallel processing, and conditional logic.
  • Agent Management: Create, configure, and manage specialized AI agents with specific models and skills.
  • Use Case: Automate a code review process where multiple specialized agents (security, performance, style) review code in parallel, followed by a synthesis agent that compiles their feedback and an orchestrator agent that manages the PR process.

Quick Start

Use the open-prose skill to run the 'examples/01-hello-world.prose' program.

Frequently Asked Questions about open-prose

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

FAQPage Schema
How do I orchestrate multiple AI agents in a single workflow?▼

You can orchestrate multiple AI agents by using a declarative programming language that defines execution semantics, manages agent lifecycles, and handles state persistence within AI sessions.

What is the best way to automate parallel processing for AI tasks?▼

The best way to automate parallel processing is to use a structured language that supports explicit execution semantics, allowing specialized agents to run concurrently and handle conditional logic for complex task automation.

Can I manage state persistence and error handling in multi-agent systems?▼

Yes, managing state persistence and error handling in multi-agent systems is supported natively through structured syntax, ensuring reliable control flow and recovery during complex task automation.

How do I define specialized AI agents for tasks like code review?▼

You define specialized AI agents by configuring them with specific models and skills in a declarative program, enabling parallel execution for tasks like security or performance reviews before synthesis.

Do I need manual prompt chaining to execute complex AI workflows?▼

No, manual prompt chaining is not needed because this approach provides a structured programming language for AI sessions, eliminating manual context management by explicitly defining control flow and agent lifecycles.

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