Package Exports
- opencode-orchestrator
Readme
OpenCode Orchestrator Plugin
Multi-Agent Plugin for OpenCode
OpenCode Orchestrator is a collaborative framework that enables low-benchmark models to deliver senior-level engineering results.
By maximizing the method of agent collaboration, we overcome the inherent limitations of individual AI models. We don't just "chat" with AI; we use a structured engineering layer to ensure complex missions are executed with 100% reliability and relentlessly pushed to completion, regardless of the model's price point.
Core Philosophy: Excellence through Collaboration
We believe that a perfect collaboration method is superior to individual intelligence.
- Systems Engineering Fusion: We integrate Operating System principles (Scheduling), Distributed Systems (Actor Model), and Algorithm Theory (Divide & Conquer) to transform unpredictable LLMs into a controlled computing resource.
- Relentless PDCA Loop: Every change follows a strict Plan-Do-Check-Act cycle. This systematic approach ensures that high-level professional tasks are completed without the quality decay or hallucinations typical of raw LLM outputs.
- Architecture over Benchmarks: By decomposing missions into atomic, verifiable tasks, we extract high-fidelity outcomes from cost-effective models, proving that superior architecture can outperform raw scale.
Why Orchestrator?
| Traditional | With Orchestrator |
|---|---|
| Expensive "Smart" Model required | Affordable Model + Smart Process |
| High Token Costs (Huge Context) | Token Efficient (Filtered Context) |
| Linear, Slow Execution | Parallel, Fast Execution |
| Errors compound silently | Self-Correcting Verification Loops |
| "Hope it works" | Strategic Micro-Tasking |
- 🧩 Strategic Organization — Maximizing output through intelligent role distribution
- 📉 Token Economy — Filtering noise to reduce costs and increase focus
- ⚡ Parallel DAG — Concurrent execution for speed and efficiency
- 🔍 Micro-Tasking — Atomic decomposition to prevent hallucinations
- 🛡️ Style Guardian — Strict AST-based linting and consistency checks
- 🔄 Self-Healing — Autonomous pivot strategies for complex errors
- 🏗️ Rust Core — Native performance for heavy lifting
How It Works (Parallel DAG)
Instead of a linear sequence, we use a Directed Acyclic Graph (DAG) to model your mission.
Mission Start (/task)
│
▼
┌───────────────┐
│ PLANNER │ (Architect)
└───────┬───────┘
│
┌───────┴───────┐
│ │ (Parallel Streams)
▼ ▼
┌───────────┐ ┌───────────┐
│ Tasks (A) │ │ Tasks (B) │
└─────┬─────┘ └─────┬─────┘
│ │
└───────┬───────┘
▼
┌───────────────┐
│ REVIEWER │ (Style Guardian)
└───────┬───────┘
▼
✅ MISSION COMPLETEInstallation
npm install -g opencode-orchestratorNote: After installation, restart OpenCode or run
opencodein your terminal. The plugin will automatically register itself in~/.config/opencode/opencode.jsonwith its absolute path.
Troubleshooting
If the command /task does not appear:
- Uninstall:
npm uninstall -g opencode-orchestrator - Clear config:
rm -rf ~/.config/opencode(Warning: resets all plugins) - Reinstall:
npm install -g opencode-orchestrator
The only command you need:
/task "Implement user authentication with JWT"The Orchestrator will:
- Decompose the mission into a JSON Task DAG
- Parallel Execute independent streams
- Search proactively for patterns
- Code with atomic precision
- Verify via the Style Guardian (MANDATORY)
- Self-Heal if errors occur
Agents
| Agent | Role |
|---|---|
| Orchestrator | Team leader — coordinates, decides, adapts |
| Planner | Breaks work into atomic tasks |
| Coder | Implements one task at a time |
| Reviewer | Quality gate — catches all errors |
| Fixer | Targeted error resolution |
| Searcher | Finds context before coding |
- System Architecture (Deep Dive): Explore the Distributed Cognitive Architecture (DCA), PDCA Loop, and Actor Model internals.
- Configuration:
opencode.tomlsetup guide.
Open Source
MIT License. No telemetry. No backdoors.
github.com/agnusdei1207/opencode-orchestrator
License
MIT License. NO WARRANTY.
🏛️ The Architecture: The PDCA & Distributed Cognitive Loop
We have moved beyond simple "chatbots". OpenCode Orchestrator implements a Deterministic Engineering Layer built on top of the stochastic nature of LLMs,
- Strict PDCA Loop: Guarantees quality via Plan-Do-Check-Act cycle.
- 🔍 Micro-tasking: Atomic decomposition to prevent hallucinations.
- 🛡️ Style Guardian: Strict AST-based linting and consistency checks by the Reviewer.
- 🔄 Self-healing: Autonomous pivoting strategies for complex errors.
- Distributed Cognitive System: Intelligence layer acting like an OS Kernel.
- File-Based State: Uses physical filesystem as RAM, ignoring context limits. We treat agents as Semantic Compute Units. By applying rigorous Computer Science principles, we achieve a level of reliability that no single model can match.
🧬 The "Grand Fusion" of Methodologies
We explicitly fused three massive domains into one seamless workflow:
PDCA Methodology (Quality Assurance):
- Plan (Planner): Recursively decomposes mission into atomic tasks ($O(log n)$).
- Do (Coder): Executes the atomic tasks in parallel (Distributed Actions).
- Check (Reviewer): Acts as a Byzantine Fault Tolerance node, strictly validating code against requirements.
- Act (Orchestrator): Merges successful states or Pivots (Dynamic Programming) if failures occur.
Distributed Systems Theory (Actor Model):
- Each agent operates as an independent Actor with isolated state.
- Context Sharding: We treat context windows like RAM, paging data in/out via
temp_contextfiles to simulate Infinite Context.
Algorithmic Efficiency:
- Divide & Conquer: Breaking complex problems into trivial $O(1)$ sub-problems.
- Dynamic Programming: Storing intermediate results (State) to avoid redundant computation and allow for intelligent backtracking.
🚀 The Command: /task
The interface to this system is a single, powerful command:
/task "Refactor the authentication middleware and implement JWT rotation"This triggers the Distributed Task Loop. It's not just a chat; it's a mission commitment.
The 5-Phase Efficiency Workflow
- 🧠 Phase 1: Filtered Analysis: The Searcher reads docs but filters out noise. We only feed the "critical path" to the Planner.
- 🌲 Phase 2: Strategic Planning: The Planner creates a JSON DAG. This is our roadmap. No token is wasted on aimless wandering.
- 🚀 Phase 3: Parallel Execution: The Orchestrator identifies independent tasks and runs them concurrently.
- 🛡️ Phase 4: Sync & Verify: The Reviewer acts as the gatekeeper. It checks syntax, logic, and cross-file consistency.
- 💰 Phase 5: Cost-Effective Completion: We achieve "Senior Developer" results at "Junior Intern" prices.
⚡ Fast-Paced Development
This project is evolving extremely fast. We iterate rapidly to bring relentless execution to your workflow. Updates are frequent. Keep your version fresh.