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agent-builder

Build DenchClaw apps that connect to the OpenClaw agent for chat sessions and tool exposure.

Updated Apr 20, 2026
Search Tags:#integration#ai#build#agent#tools#apps#denchclaw
One-click install
npx skills add https://github.com/aspectrr/denchclaw-workspace --skill agent-builder-aspectrr
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-builder
Source: https://github.com/aspectrr/denchclaw-workspace/tree/main/skills/app-builder/agent-builder
Command: npx skills add https://github.com/aspectrr/denchclaw-workspace --skill agent-builder-aspectrr

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

DenchClaw app developers need a streamlined pattern to build AI-powered apps that interact with the OpenClaw agent—managing chat sessions, streaming messages, and exposing app tools for agent invocation and memory access.

Core Features & Use Cases

  • Create chat-enabled DenchClaw apps that connect to the OpenClaw agent and manage sessions with streaming responses.
  • Expose app tools that the agent can invoke, enabling extended automation and integration with external services.
  • Use case: Build a companion app that starts a session, streams assistant messages, and calls a data-analysis tool to augment responses.

Quick Start

Create a new DenchClaw app that connects to the agent, starts a chat session, and exposes a tool for chart analysis.

Frequently Asked Questions about agent-builder

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

FAQPage Schema
How do I build AI apps that chat with an agent and stream messages?▼

To build AI apps that chat with an agent, you connect to the OpenClaw agent to manage chat sessions, stream assistant messages, and expose app tools for agent invocation. This enables extended automation and integration with external services.

What is the best way to expose app tools for agent invocation in production?▼

Exposing app tools for agent invocation requires connecting your app to the OpenClaw agent. This pattern allows the agent to invoke your app's tools during chat sessions, enabling extended automation and data-analysis integration.

How do I manage chat sessions and agent memory for AI applications?▼

Managing chat sessions and agent memory involves connecting your app to the OpenClaw agent. This secure agent communication pattern handles session management and streaming responses for production workflows.

Can I use this pattern to build a companion app that calls a data-analysis tool?▼

Yes, you can build a companion app that starts a chat session, streams assistant messages, and calls a data-analysis tool. Connecting to the OpenClaw agent enables this extended automation to augment responses.

Do I need to structure my app manifest basics differently for secure agent communication?▼

Secure agent communication requires satisfying functional requirements for app structure and manifest basics. This pattern automates building and integrating AI-powered apps with the OpenClaw agent for production workflows.

Why does my DenchClaw app need to connect to the OpenClaw agent?▼

DenchClaw apps connect to the OpenClaw agent to enable chat sessions, streaming messages, and in-app tool exposure. This integration allows the agent to access memory and invoke app tools.

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