Multi-Agent Orchestration

CodingAdvanced

Designs multi-agent pipelines that distribute complex tasks across multiple Claude Code agents for parallel processing. Includes tmux-based parallel execution, task splitting, and result integration strategies.

Trigger/agents

FrequencyFor large tasks

Senior developer? Run /agents to parallelize large-scale refactoring by module

DevOps engineer? Update configs across multiple services simultaneously

Multi-AgentParallel ProcessingAutomationPipelines

How It Works

Run /agents [task description] -> split tasks

↓

Phase 1: N agents running in parallel

agent-1

Process module A

agent-2

Process module B

agent-3

Process module C

agent-4

Process module D

↓

Integrate results + resolve conflicts

↓

✓ Parallel processing complete + merged results

Skill Code

# Multi-Agent Orchestration Skill
## Trigger: /agents [task description]

When invoked for a large task:

1. Analyze and decompose the task:
 - Identify independent subtasks
 - Check for dependencies between subtasks
 - Estimate complexity per subtask

2. Design the pipeline:
 - Split into N parallel agents
 - Assign each agent a clear scope
 - Define output format for each

3. Generate tmux orchestration:
```bash
# Create tmux session with N panes
tmux new-session -d -s agents
tmux split-window -h
tmux split-window -v
tmux select-pane -t 0 && tmux split-window -v

# Launch agents
tmux send-keys -t 0 'claude -p "Task A: [scope]"' Enter
tmux send-keys -t 1 'claude -p "Task B: [scope]"' Enter
tmux send-keys -t 2 'claude -p "Task C: [scope]"' Enter
tmux send-keys -t 3 'claude -p "Task D: [scope]"' Enter
```

4. Modern: context: fork (SKILL.md)
```markdown
---
name: parallel-worker
context: fork
---
Each sub-agent runs in an isolated context.
No shared state = no interference between agents.
```

5. After all agents complete:
 - Review each agent's output
 - Resolve conflicts if any
 - Merge results into final output

Copy and paste into your CLAUDE.md to start using immediately.

How Multi-Agent Orchestration Works

Multi-Agent Orchestration designs a pipeline where multiple Claude Code agents work in parallel — one handles tests, another refactors, a third updates docs — with a coordinator that merges results and resolves conflicts.

When to Use Multi-Agent Orchestration

Unlocks massive productivity for large-scale tasks like codebase-wide refactoring, comprehensive test suite generation, or simultaneous multi-file changes that would take hours sequentially but minutes in parallel.

Key Strengths

Parallelizes independent tasks across multiple agents
Includes conflict resolution when agents modify shared files
Scales linearly with task complexity
Automates coordination that would require manual orchestration

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