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agent-builder

Create OpenClaw agent workspaces with structured configurations and specifications.

Updated Aug 23, 2026
Search Tags:#autonomous agents#agent development#LLM architecture#OpenClaw#workspace generation
One-click install
npx skills add https://github.com/DoggyHU/pipipax_claw_backup --skill agent-builder-doggyhu
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-builder
Source: https://github.com/DoggyHU/pipipax_claw_backup/tree/main/skills/agent-builder
Command: npx skills add https://github.com/DoggyHU/pipipax_claw_backup --skill agent-builder-doggyhu

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses the challenge of building and iterating on OpenClaw agents, providing tools for creating comprehensive workspaces with predefined structures and configurations.

Core Features & Use Cases

  • End-to-End Agent Development: Design and generate the complete workspace for new agents, including personas, operating rules, and more.
  • Iterative Agent Improvement: Enhance existing agents with changes to behavior, guardrails, autonomy models, and more.
  • Use Case: Need to create a new agent for a task? Use this Skill to generate the initial workspace files, then refine the agent's behavior over time.

Quick Start

Initialize a new agent with the agent-builder skill by providing the necessary details and instructions.

Frequently Asked Questions about agent-builder

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

FAQPage Schema
How do I generate an OpenClaw agent workspace for a new autonomous task?▼

To generate an OpenClaw agent workspace, you provide the agent's purpose, autonomy level, and other specifications. The skill outputs structured workspace files, including personas and operating rules, for further development within the OpenClaw framework.

What is the process for iterating on an existing LLM agent's behavior?▼

Iterating on an existing LLM agent involves modifying its behavior, guardrails, and autonomy models within the workspace. This skill provides a structured approach to enhance existing agents by updating these predefined configurations.

Do I need to define autonomy levels before creating an OpenClaw agent?▼

Yes, you need to define autonomy levels before creating an OpenClaw agent. The workspace generation process requires input on agent purpose, autonomy level, and other specifications to output the correct operating rules and workspace files.

Can I update guardrails and operating rules for autonomous agents after initial creation?▼

Yes, you can update guardrails and operating rules for autonomous agents after initial creation. The skill supports iterative agent improvement by allowing structured changes to behavior, guardrails, and autonomy models over time.

What files are included when building an OpenClaw agent workspace?▼

When building an OpenClaw agent workspace, the generated files include predefined structures and configurations such as agent personas and operating rules. These output files provide the foundational architecture for further LLM development.

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