Multi-agent orchestration plugin for OpenCode with Boomerang Protocol support
Project description
๐ Boomerang for OpenCode
Intelligent multi-agent coordination for OpenCode โ because great software is a team sport.
๐ Vanilla OpenCode Install (One-Click Prompt)
Copy and paste the following prompt into a fresh OpenCode Builder session. It will do everything automatically.
I want you to install the Boomerang multi-agent plugin for OpenCode. Do this step by step:
1. Install the Boomerang package from PyPI. Run: pip install opencode-boomerang (or uv tool install opencode-boomerang if uv is available).
2. Install super-memory from PyPI. Run: pip install super-memory (or uv tool install super-memory if uv is available).
3. Edit the project's .opencode/opencode.json file to include:
- The Boomerang plugin: "plugin": ["opencode-boomerang"]
- An MCP server entry for super-memory with command ["super-memory"] or ["uv", "run", "super-memory"] depending on how it was installed
- An MCP server entry for sequential-thinking with command ["npx", "-y", "@modelcontextprotocol/server-sequential-thinking"]
4. Confirm completion and tell me to:
a) Restart OpenCode completely
b) After restart, open the Skills panel (type /skills) and select "boomerang-init" to run the initialization skill
๐ฏ What is Boomerang?
Boomerang is an intelligent multi-agent orchestration plugin for OpenCode that coordinates a team of specialized AI agents working together on your codebase. Instead of relying on a single AI, Boomerang implements the Boomerang Protocol โ a structured 6-step workflow that ensures thorough, consistent, and high-quality code delivery.
Think of it as your AI development team lead โ the Orchestrator plans the work, delegates to specialists, enforces quality gates, and ensures nothing falls through the cracks.
๐๏ธ Architecture
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ USER โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฌโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ
โผ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ ๐ฏ ORCHESTRATOR (Kimi K2.5) โ
โ โข Plans task execution & dependency graph โ
โ โข Delegates to specialized sub-agents โ
โ โข Enforces quality gates โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโฌโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ
โโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโ
โ โ โ
โผ โผ โผ
โโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโ
โ ๐ป โ โ ๐๏ธ โ โ ๐ โ
โ CODER โ โ ARCHITECT โ โ EXPLORER โ
โ MiniMax M2.7โ โ Kimi K2.5 โ โ MiniMax M2.7โ
โโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโ
โ โ โ
โโโโโโโโโโโโโโโโโโโโโผโโโโโโโโโโโโโโโโโโโโ
โ
โผ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
โ ๐ THE BOOMERANG PROTOCOL โ
โ โ
โ 1๏ธโฃ Memory โ 2๏ธโฃ Think โ 3๏ธโฃ Delegate โ
โ 4๏ธโฃ Git Check โ 5๏ธโฃ Quality Gates โ 6๏ธโฃ Save Memory โ
โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
The 6-Step Boomerang Protocol
| Step | Name | Description |
|---|---|---|
| 1๏ธโฃ | Memory | Query super-memory for context, past decisions, and learnings |
| 2๏ธโฃ | Think | Analyze task, build dependency graph, plan execution |
| 3๏ธโฃ | Delegate | Assign work to appropriate sub-agents by specialty |
| 4๏ธโฃ | Git Check | Verify changes, stage, and commit with proper discipline |
| 5๏ธโฃ | Quality Gates | Run lint, typecheck, and tests before completion |
| 6๏ธโฃ | Save Memory | Persist decisions and context back to super-memory |
๐ค Agent Roster
| Agent | Model | Role |
|---|---|---|
| boomerang | Kimi K2.5 | ๐ฏ Orchestrator โ Plans, coordinates, enforces protocol |
| boomerang-coder | MiniMax M2.7 | ๐ป Fast code generation โ Write and modify code efficiently |
| boomerang-architect | Kimi K2.5 | ๐๏ธ Design decisions โ Trade-off analysis and architecture |
| boomerang-explorer | MiniMax M2.7 | ๐ Codebase exploration โ Find files, search patterns, understand structure |
| boomerang-tester | MiniMax M2.7 | ๐งช Testing specialist โ Unit/integration tests, verification |
| boomerang-linter | MiniMax M2.7 | โ Quality enforcement โ Lint, format, style consistency |
| boomerang-git | MiniMax M2.7 | ๐ฆ Version control โ Commits, branches, history discipline |
| researcher | MiniMax M2.7 | ๐ Web research โ Search, fetch, and synthesize online information |
๐ง Super-Memory Integration
โ ๏ธ SUPER-MEMORY IS REQUIRED โ Boomerang will not function without it.
Why is super-memory required?
Unlike simple context windows, super-memory provides persistent long-term memory across sessions. When you start a new OpenCode session, Boomerang agents automatically:
- Query memory at start โ Retrieve relevant context, past decisions, and learnings from previous sessions
- Save memory at end โ Persist key decisions, code patterns, and project-specific knowledge
This means Boomerang learns your codebase over time and doesn't repeat mistakes.
Installation
# Using uv (recommended)
uv tool install super-memory
# Or using pip
pip install super-memory
Configuration
Add super-memory to your global ~/.opencode/opencode.json:
{
"mcp": {
"super-memory": {
"type": "local",
"command": ["super-memory"],
"enabled": true
}
}
}
Note: If you installed with
uv run, use"command": ["uv", "run", "super-memory"]
Verify Installation
super-memory --version
๐ Prerequisites
| Dependency | Status | Installation |
|---|---|---|
| super-memory | โ ๏ธ Required | uv tool install super-memory or pip install super-memory |
| searxng | ๐ง Optional | Docker: docker run -d -p 8080:8080 --name searxng searxng/searxng |
| sequential-thinking | โ Usually pre-installed | MCP server: npx -y @modelcontextprotocol/server-sequential-thinking |
๐ Installation
โญ For the easiest install experience, use the "Vanilla OpenCode Install" prompt above โ just copy, paste, and let OpenCode do everything!
Option 2: Manual Install
- Install Boomerang from PyPI:
pip install opencode-boomerang # Or if using uv uv tool install opencode-boomerang
- Install super-memory from PyPI:
pip install super-memory # Or if using uv uv tool install super-memory
- Update your
.opencode/opencode.jsonto include the plugin:{ "plugin": ["opencode-boomerang"] }
- Add super-memory and sequential-thinking MCP configurations (see Configuration section below)
- Start OpenCode and run
/boomerang-initskill - Restart OpenCode for agents to load
โ๏ธ Configuration
Example opencode.json
{
"plugin": ["opencode-boomerang"],
"mcp": {
"super-memory": {
"type": "local",
"command": ["super-memory"],
"enabled": true
},
"searxng": {
"type": "local",
"command": ["npx", "-y", "mcp-searxng"],
"environment": { "SEARXNG_URL": "http://localhost:8080" },
"enabled": false
},
"sequential-thinking": {
"type": "local",
"command": ["npx", "-y", "@modelcontextprotocol/server-sequential-thinking"],
"enabled": true
}
}
}
Key Configuration Points
| Setting | Description |
|---|---|
plugin |
Path to Boomerang plugin dist directory |
mcp.super-memory |
Required โ Long-term memory for agents |
mcp.searxng |
Optional โ Web search capabilities |
mcp.sequential-thinking |
Usually pre-installed โ Chain of thought reasoning |
๐ The Boomerang Protocol (Detailed)
Every Boomerang session follows this strict protocol:
Step 1: Memory Query
At session start, agents query super-memory for:
โข Previous decisions and rationale
โข Project-specific patterns and conventions
โข Known issues and workarounds
โข User preferences and habits
Step 2: Think & Plan
The Orchestrator:
โข Breaks down the task into subtasks
โข Identifies dependencies between subtasks
โข Builds an execution DAG (Directed Acyclic Graph)
โข Determines which agents to delegate to
Step 3: Delegate
Sub-agents are invoked based on specialty:
โข Code generation โ boomerang-coder
โข Design review โ boomerang-architect
โข Exploration โ boomerang-explorer
โข Testing โ boomerang-tester
โข Quality โ boomerang-linter
โข Version control โ boomerang-git
Step 4: Git Check
Before any work is considered complete:
โข git status shows clean working tree (or changes staged)
โข Commits are made with descriptive messages
โข Branches are properly managed
Step 5: Quality Gates
Mandatory checks before completion:
โ Lint passes (boomerang-linter)
โ Typecheck passes (where applicable)
โ Tests pass (boomerang-tester)
โ No regression in existing functionality
Step 6: Save Memory
At session end, critical information is saved:
โข Key architectural decisions
โข Code patterns established
โข Lessons learned
โข User preferences
๐ฅ Release Pipeline & Updating
When a new version of Boomerang is released:
1. Check for Updates
gh release view Veedubin/opencode-boomerang --json tagName,createdAt
2. Update Your Installation
# Update Boomerang from PyPI
pip install --upgrade opencode-boomerang
# Or if using uv
uv tool upgrade opencode-boomerang
# Re-run initialization
opencode /boomerang-init
3. Verify Installation
# Check the version in your installed plugin
cat .opencode/plugins/boomerang/package.json | grep version
๐ Release Package Contents
The boomerang.tar.gz release contains:
.opencode/
โโโ agents/ # Agent definitions
โ โโโ boomerang.md # Orchestrator
โ โโโ boomerang-coder.md # Code generation
โ โโโ boomerang-architect.md # Architecture
โ โโโ boomerang-explorer.md # Exploration
โ โโโ boomerang-tester.md # Testing
โ โโโ boomerang-linter.md # Linting
โ โโโ boomerang-git.md # Git operations
โ โโโ researcher.md # Web research
โโโ skills/ # Boomerang skills
โ โโโ boomerang-architect/
โ โโโ boomerang-coder/
โ โโโ boomerang-init/
โ โโโ boomerang-orchestrator/
โ โโโ boomerang-tester/
โโโ plugins/boomerang/ # Plugin implementation
โโโ dist/ # Compiled JavaScript
โโโ package.json
๐ License
MIT License โ see LICENSE for details.
Built with ๐ by Veedubin
Your AI development team, on demand.
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