opencode-dev

Configure AI agents, custom tools, and MCP servers in OpenCode.

3|Updated Mar 6, 2026

Search Tags:#developer tools #workflow automation #ai agent #configuration management #opencode

Ready to run

npx skills add https://github.com/benjaminwestern/google-engineer-skills --skill opencode-dev

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: opencode-dev
Source: https://github.com/benjaminwestern/google-engineer-skills/tree/main/skills/opencode-dev
Command: npx skills add https://github.com/benjaminwestern/google-engineer-skills --skill opencode-dev

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill streamlines the creation and management of AI agents, custom tools, and workflows within the OpenCode ecosystem, simplifying complex AI development setups.

Core Features & Use Cases

Agent Creation: Define and configure AI agents using Markdown or JSON.
Tool Development: Create custom command-line tools with parameter validation.
Workflow Orchestration: Design multi-agent workflows for complex tasks.
Use Case: You need to set up a new AI agent that can review code and write documentation. Use this Skill to quickly define the agent's prompt, permissions, and tools.

Quick Start

Use the opencode-dev skill to create a new agent named 'code-analyzer' with subagent mode.

Frequently Asked Questions about opencode-dev

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

FAQPage Schema

How do I create and configure AI agents using Markdown or JSON?▼

You create and configure AI agents by defining their prompts, permissions, and tools in Markdown or JSON files. This approach provides a structured development environment that ensures reproducible agent behaviors within the OpenCode framework.

What is the best way to define custom command-line tools with parameter validation for AI agents?▼

Defining custom command-line tools with parameter validation is best handled by specifying shell commands and parameters within configuration files. This ensures structured tool development and reproducible agent behaviors across different environments.

How does inter-agent communication work in a multi-agent workflow?▼

Inter-agent communication works through established protocols that enable multiple AI agents to orchestrate complex tasks. Setting up these communication protocols allows you to design structured workflows where agents interact predictably.

Can I use shell commands to build custom tools for AI agents?▼

Yes, you can use shell commands to build custom tools for AI agents. The framework supports defining shell commands and parameters for custom tools, allowing you to create tailored command-line utilities with parameter validation.

Do I need MCP servers to manage AI agents and custom tools?▼

Setting up MCP servers is supported to facilitate the development and management of AI agents and custom tools. They help address the need for structured AI development environments and reproducible agent behaviors.

What are the limitations of managing AI agents with configuration files?▼

While configuration files via Markdown and JSON provide structured AI development environments, they require manual setup for inter-agent communication protocols and custom tool parameter validation, which may limit dynamic, real-time workflow adjustments.