agent-forge

Create and improve OpenClaw skills and agents through structured design workflows.

44|9|Updated Mar 9, 2026
One-click install
npx skills add https://github.com/AlekseiUL/agentforge-openclaw --skill agent-forge
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: agent-forge
Source: https://github.com/AlekseiUL/agentforge-openclaw/tree/main
Command: npx skills add https://github.com/AlekseiUL/agentforge-openclaw --skill agent-forge

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill solves the problem of creating inconsistent OpenClaw skills and agents by providing a repeatable production workflow with templates, validation steps, memory patterns, and improvement practices.

Core Features & Use Cases

  • Skill Creation Workflow: Guides users through designing, structuring, validating, and testing reusable OpenClaw skills with appropriate triggers and examples.
  • Agent Architecture Design: Helps create OpenClaw agents with roles, tools, workspaces, memory systems, team coordination, and operational safeguards.
  • Skill and Agent Improvement: Provides audit and upgrade processes for existing agents and skills using targeted fixes, quality checks, and iteration patterns.

Quick Start

Ask the agent-forge skill to create a new OpenClaw skill or agent for a specific purpose and guide you through the required setup process.

Frequently Asked Questions about agent-forge

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

FAQPage Schema
How do I create reusable AI agents with structured memory architecture?

To create reusable AI agents with structured memory architecture, use a production workflow that guides you through defining agent roles, configuring tools, setting up workspaces, and establishing operational safeguards for reliable deployment.

What is a structured workflow for building production-ready AI skills?

A structured workflow for building production-ready AI skills involves designing, structuring, validating, and testing reusable skill definitions using frontmatter templates and operational quality checks to ensure consistent deployment.

How do I validate and test AI agent configurations before deployment?

You validate and test AI agent configurations before deployment by applying production checklists and operational quality checks that audit the agent setup, memory systems, and triggers for reliable execution.

Can I improve existing AI agents without rebuilding them from scratch?

Yes, you can improve existing AI agents without rebuilding them from scratch by using targeted audit and upgrade processes that apply quality checks, iteration patterns, and targeted fixes to current configurations.

Do I need frontmatter-based definitions to build OpenClaw agents?

Yes, frontmatter-based definitions are required to build OpenClaw agents, as they provide the necessary templates and configuration patterns needed to establish roles, triggers, and memory architecture correctly.

What's the best way to set up team coordination and workspaces for AI agents?

The best way to set up team coordination and workspaces for AI agents is through structured architecture design that defines roles, assigns tools, and configures memory systems with operational safeguards.