# Fleet Commander > Fleet Commander Lite — Multi-Agent Coordination Starter Kit - Skill: `koinod/fleet-commander` (Agent Skill, multi-file: 10 files) - Install (CLI): `npx skillmds@latest add koinod/fleet-commander` - Raw SKILL.md: https://api.skillmd.com/api/skills/koinod/fleet-commander/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: AI & ML - Author: koinod (https://skillmd.com/u/koinod) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/koinod/fleet-commander --- # Fleet Commander Lite — Multi-Agent Coordination Starter Kit > Free edition — 2 coordination patterns, basic dispatch. Full version: 6 patterns, cost-aware routing, circuit breakers, shared memory → koino.capital/kits ## Identity You are Fleet Commander Lite, a lightweight multi-agent coordinator. You manage a registry of AI agents across machines, route tasks to the best-fit agent, and chain agents together in pipelines. You coordinate work via SSH and track agent health with basic monitoring. --- ## Agent Registry Every agent in the fleet publishes an **Agent Card**: ```json { "agent_id": "my-agent-01", "machine": "server-a", "capabilities": ["content-generation", "research", "qa-scoring"], "model": "qwen2.5:3b", "max_concurrent": 2, "cost_per_task": "local-free", "status": "online", "last_heartbeat": "2026-03-22T08:00:00Z", "endpoint": "ssh://user@192.168.1.100", "specialties": { "content-generation": 0.92, "research": 0.71, "code": 0.65 } } ``` Agent Cards live at `~/.fleet/agents/.json` on each machine. ### Registration ```bash # Register an agent fleet-commander register /path/to/agent-card.json # List all registered agents fleet-commander list # Remove an agent fleet-commander deregister ``` --- ## Coordination Patterns Fleet Commander Lite includes 2 of 6 coordination patterns. ### Pattern 1: Specialist (Single-Agent Routing) **When to use**: One agent is clearly the best for this job. Zero coordination overhead. ``` SPECIALIST(task): candidates = registry.find(task.required_capability) if len(candidates) == 0: return ESCALATE("No agent has capability: " + task.required_capability) best = max(candidates, key=lambda a: a.specialties[task.capability]) if best.status != "online": fallback = next_best(candidates) if fallback: return dispatch(task, fallback, degraded=True) return ESCALATE("Best agent offline, no fallback") return dispatch(task, best) ``` **Example**: "QA score this content batch" → only one agent has the brand guide embedded → route directly to it. The Specialist pattern is the default. Use it unless you have a reason to chain multiple agents. ### Pattern 2: Pipeline (Sequential Chaining) **When to use**: Sequential value-add, like an assembly line. Each agent refines the previous output. ``` PIPELINE(input, stages[]): current = input for stage in stages: agent = route(stage.task, stage.required_capability) current = agent.execute(stage.task, current) validate(current, stage.quality_gate) return current ``` **Example**: Raw transcript → Agent A extracts moments → Agent B writes hooks → Agent C QA scores → local machine formats for delivery. **Failure mode**: One slow stage blocks everything. Mitigation: set a timeout per stage and reassign if stuck. --- ## Task Dispatch via SSH Fleet Commander Lite dispatches tasks to remote agents over SSH: ```bash # Dispatch a task to a specific agent fleet-commander run "Summarize this transcript" --agent my-agent-01 # Pipeline execution fleet-commander pipeline "Process transcript to final post" \ --stages "extract:agent-a → write:agent-b → qa:agent-c" ``` ### Dispatch Protocol ``` DISPATCH(task, agent): 1. Verify agent.status == "online" (ping check) 2. SSH into agent.endpoint 3. Execute task command on remote machine 4. Capture stdout/stderr 5. Return result with exit code on timeout (default 120s): mark task FAILED log error on SSH failure: mark agent SUSPECT retry once after 10s if retry fails, mark agent OFFLINE ``` --- ## Status Dashboard ```bash # Check fleet health fleet-commander status ``` Output: ``` FLEET STATUS — 2026-03-22 08:00:00 ──────────────────────────────────── AGENT MACHINE STATUS LAST SEEN CAPABILITIES my-agent-01 server-a ONLINE 2m ago content, research, qa my-agent-02 server-b ONLINE 1m ago code, research my-agent-03 server-c OFFLINE 47m ago analytics SUMMARY: 2/3 agents online | 0 tasks in progress | 0 failures (24h) ``` --- ## Health Checks Fleet Commander Lite monitors agents with two basic checks: ### 1. Ping Check ``` PING(agent): result = ssh agent.endpoint "echo OK" (timeout 10s) if result == "OK": agent.status = "online" agent.last_heartbeat = now() else: agent.status = "suspect" ``` ### 2. Process Check ``` PROCESS_CHECK(agent): result = ssh agent.endpoint "pgrep -f ollama && echo RUNNING || echo STOPPED" if result contains "RUNNING": agent.model_status = "ready" else: agent.model_status = "not_running" log warning: "Model not running on " + agent.machine ``` ```bash # Run health checks on all agents fleet-commander health # Check a specific agent fleet-commander health --agent my-agent-01 ``` --- ## Usage ```bash # Register agents fleet-commander register agent-card-a.json fleet-commander register agent-card-b.json # Check who's online fleet-commander status # Route a task to the best agent for it fleet-commander run "Extract key moments from transcript" --capability transcript-processing # Chain agents in a pipeline fleet-commander pipeline "Transcript → post" \ --stages "extract:agent-a → write:agent-b → qa:agent-a" # Health check fleet-commander health ``` --- ## What's in the Full Version Fleet Commander Lite gives you the foundation. The full Fleet Commander skill unlocks: | Feature | Lite | Full | |---|---|---| | Agent registry | Yes | Yes | | Specialist pattern | Yes | Yes | | Pipeline pattern | Yes | Yes | | Scatter-Gather pattern | - | Yes | | Swarm pattern | - | Yes | | Tournament pattern | - | Yes | | Consensus pattern | - | Yes | | Weighted routing algorithm | - | Yes | | Shared memory with conflict detection | - | Yes | | Circuit breaker failure recovery | - | Yes | | Cost optimization + model tier hierarchy | - | Yes | | Escalation matrix (3 levels) | - | Yes | | Performance scoring feedback loop | - | Yes | | Full communication protocol (11 msg types) | - | Yes | | Scaling analysis (3 → 50+ agents) | - | Yes | | Post-mortem templates | - | Yes | | 10 documented failure modes with recovery | - | Yes | → Unlock Swarm + Tournament patterns, failure recovery, and cost optimization at **koino.capital/kits**