openclaw

Name: openclaw
Availability: InStock
Author: javierhbr

Create and manage autonomous agent factories with multi-agent coordination via YAML files.

Updated Feb 5, 2026

Search Tags:#automation #workflow #agent #multi-agent #orchestration #coordination

Ready to run

npx skills add https://github.com/javierhbr/agnostic-agent-loop --skill openclaw-javierhbr

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: openclaw
Source: https://github.com/javierhbr/agnostic-agent-loop/tree/main/internal/skills/packs/openclaw
Command: npx skills add https://github.com/javierhbr/agnostic-agent-loop --skill openclaw-javierhbr

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill provides a framework for building and running autonomous agent factories, enabling complex multi-agent workflows and parallel task execution.

Core Features & Use Cases

Orchestration: Manages task flow, spawns worker agents, and synthesizes results.
Coordination: Utilizes shared state files (reservations.yaml, announcements.yaml, kill-signals.yaml) for inter-agent communication.
Role Specialization: Supports distinct agent roles like Orchestrator, Worker, Researcher, and Reviewer.
Use Case: Set up an autonomous system to research a market opportunity, pitch a new app idea, implement the core features, and review the code, all coordinated by the OpenClaw framework.

Quick Start

Use the openclaw skill to set up an orchestrator for managing parallel task execution.

Frequently Asked Questions about openclaw

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

FAQPage Schema

How do I build autonomous agent factories for parallel task execution?▼

You can build autonomous agent factories by using a multi-agent coordination pattern that manages task flow, spawns worker agents, and synthesizes results to enable parallel task execution.

How does multi-agent coordination work for task state synchronization?▼

Multi-agent coordination works by using shared YAML files for inter-agent communication, allowing agents to manage tasks, synchronize state, and handle errors through defined protocols.

What agent roles are needed to orchestrate complex multi-agent workflows?▼

Complex multi-agent workflows require specialized agent roles such as orchestrator, worker, researcher, and reviewer to manage distinct phases of task execution and synthesis.

Do I need external dependencies to set up an orchestrator for autonomous agents?▼

No external dependencies are required to set up an orchestrator for autonomous agents, as the framework relies entirely on internal scripts and shared YAML files for coordination.

What is the best way to handle error management in multi-agent automation workflows?▼

The best way to handle error management in multi-agent automation workflows is by utilizing shared state files like kill-signals.yaml to communicate failures and coordinate error handling across agents.

Can I use shared YAML files for researching and reviewing code in a single automated workflow?▼

Yes, you can use shared YAML files to coordinate an automated workflow where a researcher agent gathers data, a worker implements features, and a reviewer agent evaluates the code.