AI Coding Agent Orchestration

Tip

This guide is for software engineers with different levels of AI-assisted coding experience. It explains why an AI coding agent CLI can be useful, then walks through a practical OpenCode setup with plugins, skills, and integrations.

Note

This is an opinionated selection of tools and instructions based on personal experience. The AI tooling ecosystem changes quickly, so treat this as a starting point and adapt it to your own workflow.

MIT License

---

Who this is for

• Developers who already use AI coding assistance in an IDE and want to understand when a CLI agent adds value.
• Engineers who want a repeatable OpenCode setup for local development, documentation, context, and external tools.
• Advanced users who want to extend coding agents with skills, MCP servers, LSPs, Jira, Azure DevOps, and Azure integrations.

Parts 1 and 2 are accessible to anyone interested in AI-assisted development. Part 3 is more advanced and focuses on optional tooling, custom skills, and integrations.

How to read this guide

Start with Part 1 if you are new to AI coding agents. Go directly to Part 2 if you already understand the concepts and want the default setup. Use Part 3 as a reference when you are ready to extend the environment.

Guide parts

1. Part 1: Why Use an AI Coding Agent CLI?
   Explains the evolution from chat and IDE completion to agentic CLI workflows, the agent loop, context management, and the tool landscape.

2. Part 2: A default setup
   Provides the practical setup path: installing OpenCode, adding context, configuring tools, installing skill packs, and adopting daily-use habits.

3. Part 3: Advanced Use
   Covers optional advanced additions such as engineering skills, custom review workflows, SQL LSP support, Jira workflows, Azure DevOps, and Azure MCP integration.

Contribution

Questions, corrections, and suggestions are welcome. Open an issue at CodingAgentOrchestration issues or contribute with a pull request.