481 lines
13 KiB
Markdown
481 lines
13 KiB
Markdown
---
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name: distributed-gummy
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description: Orchestrate gummy-agents across distributed network using 'd' command for load-balanced, multi-host AI development
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---
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# Distributed Gummy Orchestrator
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Coordinate gummy-agent tasks across your Tailscale network using the `d` command for intelligent load balancing and multi-host AI-powered development.
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## When to Use
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This skill activates when you want to:
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✅ **Distribute gummy tasks across multiple hosts**
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- "Run this gummy task on the least loaded host"
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- "Execute specialist on optimal node"
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- "Distribute testing across all machines"
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✅ **Load-balanced AI development**
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- "Which host should handle this database work?"
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- "Run API specialist on best available node"
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- "Balance gummy tasks across cluster"
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✅ **Multi-host coordination**
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- "Sync codebase andw run gummy on node-2"
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- "Execute parallel specialists across network"
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- "Run tests on all platforms simultaneously"
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✅ **Network-wide specialist monitoring**
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- "Show all running specialists across hosts"
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- "What gummy tasks are active on my network?"
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- "Status of distributed specialists"
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## How It Works
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### Architecture
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```
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[Main Claude] ──> [Orchestrator] ──> dw command ──> [Network Nodes]
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│ │
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├──> Load Analysis ├──> gummy-agent
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├──> Host Selection ├──> Specialists
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├──> Sync Management └──> Tasks
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└──> Task Distribution
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```
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### Core Workflows
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**1. Load-Balanced Execution**
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```bash
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# User request: "Run database optimization on best host"
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# Agent:
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1. Execute: dw load
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2. Parse metrics (CPU, memory, load average)
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3. Calculate composite scores
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4. Select optimal host
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5. Sync codebase: dw sync <host>
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6. Execute: dw run <host> "cd <project> && gummy task 'optimize database queries'"
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```
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**2. Parallel Distribution**
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```bash
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# User request: "Test on all platforms"
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# Agent:
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1. Get hosts: dw status
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2. Filter by availability
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3. Sync all: for host in hosts; do dw sync $host; done
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4. Launch parallel: dw run host1 "test" & dw run host2 "test" & ...
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5. Aggregate results
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```
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**3. Network-Wide Monitoring**
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```bash
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# User request: "Show all specialists"
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# Agent:
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1. Get active hosts: dw status
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2. For each host: dw run <host> "gummy-watch status"
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3. Parse specialist states
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4. Aggregate and display
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```
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## Available Scripts
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### orchestrate_gummy.py
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Main orchestration logic - coordinates distributed gummy execution.
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**Functions**:
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- `select_optimal_host()` - Choose best node based on load
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- `sync_and_execute_gummy()` - Sync code + run gummy task
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- `parallel_gummy_tasks()` - Execute multiple tasks simultaneously
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- `monitor_all_specialists()` - Aggregate specialist status across network
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**Usage**:
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```python
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from scripts.orchestrate_gummy import select_optimal_host, sync_and_execute_gummy
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# Find best host
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optimal = select_optimal_host(task_type="database")
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# Returns: {'host': 'node-1', 'score': 0.23, 'cpu': 15%, 'mem': 45%}
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# Execute on optimal host
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result = sync_and_execute_gummy(
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host=optimal['host'],
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task="optimize user queries",
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project_dir="/path/to/project"
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)
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```
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### d_wrapper.py
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Wrapper for `d` command operations.
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**Functions**:
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- `get_load_metrics()` - Execute `dwload` and parse results
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- `get_host_status()` - Execute `dwstatus` and parse availability
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- `sync_directory()` - Execute `dwsync` to target host
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- `run_remote_command()` - Execute `dwrun` on specific host
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## Workflows
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### Workflow 1: Load-Balanced Task Distribution
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**User Query**: "Run database optimization on optimal host"
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**Agent Actions**:
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1. Call `get_load_metrics()` to fetch cluster load
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2. Call `select_optimal_host(task_type="database")` to choose best node
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3. Call `sync_directory(host, project_path)` to sync codebase
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4. Call `dwrun <host> "cd project && gummy task 'optimize database queries'"`
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5. Monitor execution via `gummy-watch`
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6. Return results
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### Workflow 2: Parallel Multi-Host Execution
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**User Query**: "Run tests across all available nodes"
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**Agent Actions**:
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1. Call `get_host_status()` to get available hosts
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2. Filter hosts by availability and capability
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3. For each host:
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- Sync codebase: `sync_directory(host, project)`
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- Launch test: `dwrun <host> "cd project && gummy task 'run test suite'" &`
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4. Collect all background job PIDs
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5. Wait for completion
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6. Aggregate results from all hosts
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### Workflow 3: Network-Wide Specialist Monitoring
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**User Query**: "Show all running specialists across my network"
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**Agent Actions**:
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1. Get active hosts from `dwstatus`
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2. For each host:
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- Check for gummy-agent: `dwrun <host> "command -v gummy"`
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- If present, get specialists: `dwrun <host> "ls -la ~/.gummy/specialists"`
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3. Parse specialist metadata from each host
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4. Create aggregated dashboard showing:
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- Host name
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- Active specialists
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- Session states (active/dormant)
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- Resource usage
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5. Display unified network view
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### Workflow 4: Intelligent Work Distribution
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**User Query**: "I have database work and API work - distribute optimally"
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**Agent Actions**:
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1. Analyze tasks:
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- Task 1: database optimization (CPU-intensive)
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- Task 2: API development (I/O-intensive)
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2. Get load metrics for all hosts
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3. Select hosts using different criteria:
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- Database work → host with lowest CPU load
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- API work → host with lowest I/O wait
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4. Sync to both hosts
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5. Launch tasks in parallel:
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```bash
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dw run <cpu-host> "gummy task 'optimize database queries'" &
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dw run <io-host> "gummy task 'build REST API endpoints'" &
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```
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6. Monitor both executions
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7. Report when complete
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## Error Handling
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### Connection Issues
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```python
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try:
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result = d_run(host, command)
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except SSHConnectionError:
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# Retry with different host
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fallback = select_optimal_host(exclude=[failed_host])
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result = d_run(fallback, command)
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```
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### Sync Failures
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```python
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if not sync_successful:
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# Fall back to local execution
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return execute_local_gummy(task)
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```
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### Load Metric Unavailable
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```python
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if not load_data:
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# Use round-robin distribution
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return round_robin_host_selection()
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```
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## Performance & Caching
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**Load Metrics Caching**:
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- Cache TTL: 30 seconds (load changes fast)
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- Cache location: `/tmp/d-load-cache.json`
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- Invalidate on manual request
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**Host Availability**:
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- Cache TTL: 60 seconds
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- Cache location: `/tmp/d-status-cache.json`
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**Specialist State**:
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- Cache TTL: 5 seconds (near real-time)
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- Only cached during active monitoring
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## Keywords for Auto-Detection
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This skill activates when user mentions:
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**Distributed Operations**:
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- distributed, cluster, network, multi-host, across hosts, all nodes, all machines
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- remote, ssh, tailscale
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**Gummy Integration**:
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- gummy, specialist, agent, haiku, task
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- execute gummy, run gummy, gummy task
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**Load Balancing**:
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- least loaded, best host, optimal node, load balance, best machine
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- which host should, where should I run
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**Coordination**:
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- sync andw run, parallel, coordinate, orchestrate, distribute
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- run on, execute on, send to
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**Monitoring**:
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- all specialists, network status, cluster status, show specialists
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- what's running, active tasks
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**Examples That Activate**:
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- "Run database optimization on least loaded host"
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- "Execute API specialist on optimal node"
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- "Distribute tests across all machines"
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- "Show all specialists across network"
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- "Sync codebase andw run gummy on node-2"
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- "Which host should handle this database work?"
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- "Run parallel gummy tasks across cluster"
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**Does NOT Activate** (local operations):
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- "Run gummy task locally"
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- "Execute specialist here"
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- "/gummy-task add logging"
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## Usage Examples
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### Example 1: Simple Load-Balanced Execution
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```
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👤: "Run database optimization on the best available host"
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🤖: I'll find the optimal host and execute the task there.
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[Executes: dw load]
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[Analysis: node-1 has lowest composite score (0.18)]
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[Executes: dw sync node-1]
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[Executes: dw run node-1 "cd ~/project && gummy task 'optimize database queries'"]
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✅ Task launched on node-1 (CPU: 12%, Mem: 35%, Load: 0.18)
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Monitor with: ssh node-1 'gummy-watch'
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```
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### Example 2: Parallel Multi-Platform Testing
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```
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👤: "Run tests across all available nodes"
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🤖: I'll distribute test execution across your network.
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[Executes: dw status]
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[Found: 4 available hosts]
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[Syncing codebase to all hosts...]
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✓ node-1 synced
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✓ node-2 synced
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✓ node-3 synced
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✓ node-4 synced
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[Launching parallel test execution...]
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node-1: Running unit tests
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node-2: Running integration tests
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node-3: Running e2e tests
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node-4: Running performance tests
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[All tests complete in 8 minutes (vs 32 minutes sequential)]
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Results:
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✅ unit: 1,247 passed
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✅ integration: 89 passed
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✅ e2e: 34 passed
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⚠️ performance: 3 slow queries detected
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```
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### Example 3: Intelligent Task Distribution
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```
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👤: "I need to optimize database queries and build new API endpoints"
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🤖: I'll distribute these optimally based on task characteristics.
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[Analyzing tasks...]
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- Database optimization: CPU-intensive
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- API development: I/O-bound
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[Fetching cluster load...]
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node-1: CPU 15%, I/O 45% → Best for database work
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node-2: CPU 65%, I/O 12% → Best for API work
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[Distributing tasks...]
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✓ Database optimization → node-1
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✓ API development → node-2
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[Syncing and launching...]
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node-1: database-expert specialist active
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node-2: api-developer specialist active
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Both tasks running in parallel. Expected completion: 15 minutes.
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Monitor:
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ssh node-1 'gummy-watch'
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ssh node-2 'gummy-watch'
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```
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### Example 4: Network-Wide Specialist Status
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```
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👤: "Show all specialists running across my network"
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🤖: Scanning network for active specialists...
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[Checking all hosts...]
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╔═══════════════════════════════════════════════════════╗
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║ DISTRIBUTED SPECIALIST DASHBOARD ║
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╚═══════════════════════════════════════════════════════╝
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┌─ node-1 ──────────────────────────────────────────────┐
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│ ⚡ database-expert Sessions: 8 Cost: $0.02 │
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│ 💤 testing-specialist Sessions: 3 Cost: $0.01 │
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└───────────────────────────────────────────────────────┘
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┌─ node-2 ──────────────────────────────────────────────┐
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│ ⚡ api-developer Sessions: 5 Cost: $0.01 │
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│ ⚡ frontend-specialist Sessions: 12 Cost: $0.03 │
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└───────────────────────────────────────────────────────┘
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┌─ node-3 ──────────────────────────────────────────────┐
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│ 💤 security-specialist Sessions: 2 Cost: $0.01 │
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└───────────────────────────────────────────────────────┘
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Total: 5 active specialists across 3 hosts
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Total cost today: $0.08
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```
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### Example 5: Sync-Before-Execute Workflow
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```
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👤: "Sync my codebase to node-3 andw run frontend specialist there"
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🤖: I'll sync and execute on node-3.
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[Current directory: ~/projects/myapp]
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[Syncing to node-3...]
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Sending: src/ components/ lib/ package.json
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Excluding: node_modules .git dist
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✓ Synced 1,247 files (45 MB) in 3 seconds
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[Launching frontend specialist on node-3...]
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✓ specialist created (session: abc123)
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⚡ Working on task...
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Task active on node-3. Monitor: ssh node-3 'gummy-watch'
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```
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## Configuration
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### Required Tools
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- ✅ `d` command (distributed CLI)
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- ✅ `gummy-agent` installed on remote hosts
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- ✅ Tailscale network configured
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- ✅ SSH access via ~/.ssh/config
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- ✅ rsync on all hosts
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### Optional Configuration
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Create `~/.config/distributed-gummy/config.yaml`:
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```yaml
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# Load balancing weights
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load_weights:
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cpu: 0.4
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memory: 0.3
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load_average: 0.3
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# Sync exclusions
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sync_exclude:
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- node_modules
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- .git
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- dist
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- build
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- .DS_Store
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- "*.log"
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# Host preferences for task types
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host_preferences:
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database:
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- node-1 # High CPU
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frontend:
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- node-2 # High memory
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testing:
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- node-3 # Dedicated test node
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```
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## Troubleshooting
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### "Host not responding"
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```bash
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# Check Tailscale connectivity
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tailscale status
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# Check SSH access
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ssh <host> echo "OK"
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# Verify dw command works
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dw status
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```
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### "Sync failed"
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```bash
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# Manual sync test
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dw sync <host>
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# Check rsync
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which rsync
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# Check disk space on remote
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dw run <host> "df -h"
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```
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### "Gummy not found on remote host"
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```bash
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# Check gummy installation
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dw run <host> "which gummy"
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# Install if needed
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dw run <host> "brew install WillyV3/tap/gummy-agent"
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```
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## Limitations
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- Requires gummy-agent installed on all target hosts
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- Requires Tailscale network connectivity
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- Load metrics only available from `dwload` command
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- Sync uses current directory as base (change with cd first)
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## Version
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1.0.0 - Initial release
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