agent-maker

What This Skill Does

The agent-maker skill is the cornerstone for scaling your operations within OpenClaw. It serves as an intelligent architect that transforms high-level business requirements into fully functional, autonomous AI agents. Instead of manually configuring parameters, prompts, and toolsets, you engage in a guided discovery process that ensures the agent is purpose-built, secure, and aligned with your operational goals. The skill facilitates a three-phase workflow covering identity, personality, and technical architecture, culminating in an agent ready to deploy.

Installation

To begin building custom agents, run the following command in your OpenClaw terminal:

clawhub install openclaw/skills/skills/anhnt224/agent-maker-2

Ensure you have sufficient permissions to register new agent entities within your current OpenClaw workspace.

Use Cases

• Automated Customer Support: Build an agent trained on your internal documentation that handles Tier-1 support tickets and escalates complex issues to human agents.
• Market Research Analyst: Create a specialized agent capable of scraping web data, synthesizing competitive trends, and generating weekly briefing reports.
• Development Workflow Assistant: Deploy an agent configured with code-execution tools to run unit tests, audit pull requests, and manage documentation syncs.
• Content Creation Pipeline: Generate a creative writing assistant that adheres to your brand voice, handles social media scheduling, and creates cross-platform content.

Example Prompts

1. "I need to build an agent that monitors our support channel, summarizes recurring bugs, and updates our JIRA board automatically."
2. "Can you help me set up a research agent that is strictly formal, uses Claude 3.5 Sonnet, and focuses on analyzing financial market trends?"
3. "Start the agent creation process. I want a personal assistant that manages my calendar and reminds me of high-priority tasks."

Tips & Limitations

• Iterative Discovery: The agent-maker works best when you are specific about the agent's constraints. If the initial setup isn't precise enough, ask the agent to 'refine personality' or 'add more tools' to an existing bot.
• Model Selection: Always match your model to the task. Use Opus for high-reasoning tasks and Haiku for high-volume, low-latency automation to optimize your credit usage.
• Security: While the agent-maker configures basic security, always review the 'permissions' manifest after creation to ensure the agent only has access to the APIs and file paths it truly needs.