cross-machine-coordination

Skill: Cross-Machine Coordination Pattern

Skill ID: cross-machine-coordination
Owner: Ralph (Work Monitor)
Squad Integration: All agents
Status: Specification (ready for implementation)

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Overview

Enables squad agents running on different machines (laptop, DevBox, Azure VM) to securely share work, coordinate execution, and pass results without manual intervention.

Pattern: Git-based task queuing + GitHub Issues supplement

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Usage

For Task Sources (Orchestrating Machine)

To assign work to DevBox:

# Create task file
cat > .squad/cross-machine/tasks/2026-03-14T1530Z-laptop-gpu-voice-clone.yaml << 'EOF'
id: gpu-voice-clone-001
source_machine: laptop-machine
target_machine: devbox
priority: high
created_at: 2026-03-14T15:30:00Z
task_type: gpu_workload
payload:
  command: "python scripts/voice-clone.py --input voice.wav --output cloned.wav"
  expected_duration_min: 15
  resources:
    gpu: true
    memory_gb: 8
status: pending
EOF

# Commit & push
git add .squad/cross-machine/tasks/
git commit -m "Cross-machine task: GPU voice cloning [squad:machine-devbox]"
git push origin main

Ralph on DevBox will:

1. Pull the task on next cycle (5-10 min)
2. Validate schema & command whitelist
3. Execute the GPU workload
4. Write result to .squad/cross-machine/results/gpu-voice-clone-001.yaml
5. Commit & push the result

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For Task Executors (DevBox, Azure VMs)

Ralph automatically watches .squad/cross-machine/tasks/ for work targeted at this machine.

On each cycle (5-10 min):

# Pseudo-code (Ralph implementation)
1. git pull origin main
2. Load all .yaml files in .squad/cross-machine/tasks/
3. Filter for status=pending AND target_machine=HOSTNAME
4. For each task:
   a. Validate schema (must have: id, source_machine, target_machine, payload)
   b. Validate command against whitelist
   c. Execute task (with timeout)
   d. Write result to .squad/cross-machine/results/{id}.yaml
   e. Commit & push result