Ollama Herd ships with a ClawHub skill that gives AI agents instant knowledge of your fleet. Install it once and any OpenClaw-compatible agent can check node health, route requests, pull models, run diagnostics, and manage your fleet, all through natural language.
What the Skill Does
The Ollama Herd skill teaches your AI agent:
- Fleet operations, check node status, queue depths, loaded models, health scores
- Request routing, send LLM, embedding, image generation, and speech-to-text requests through the fleet
- Model management, pull models to specific nodes, list available models, check hot vs. cold state
- Diagnostics, query the trace database, read JSONL logs, identify slow requests and bottlenecks
- Health monitoring, 30+ automated health checks covering offline nodes, memory pressure, thermal throttling, model thrashing, error rates, and more
- Dashboard access, point users to the real-time web dashboard for visual monitoring
Install
clawhub install ollama-herd
Or search for it on ClawHub:
clawhub search "ollama herd"
What Your Agent Can Do After Install
Check fleet health:
"How's my Ollama fleet doing?"
The agent hits /fleet/status and /dashboard/api/health, then summarizes node status, loaded models, queue depths, and any health warnings.
Route a request:
"Ask llama3.3:70b to explain quicksort"
The agent sends the request through the fleet router. Herd picks the best node automatically.
Pull a model:
"Pull codestral onto the Mac Studio"
The agent calls /api/pull with the target node. Streams progress in real time.
Diagnose issues:
"Why were my responses slow yesterday?"
The agent queries the trace database for high-latency entries, checks for thermal throttling or memory pressure events, and reports what it finds.
Get recommendations:
"What models should I run on each machine?"
The agent hits /dashboard/api/recommendations for AI-powered model mix suggestions based on your hardware and usage patterns.
Supported Platforms
The skill works with Ollama Herd on macOS, Linux, and Windows. Platform-specific features (image generation, speech-to-text, meeting detection) are noted in the skill and the agent adapts its suggestions accordingly.
API Endpoints the Skill Uses
| Endpoint | Purpose |
|---|---|
GET /fleet/status |
Full fleet state, nodes, models, queues |
GET /fleet/queue |
Lightweight queue depths for backoff |
POST /api/chat |
Ollama-format chat completions |
POST /v1/chat/completions |
OpenAI-format chat completions |
POST /api/pull |
Pull models onto fleet nodes |
GET /api/tags |
List all available models |
GET /api/ps |
List models currently loaded in memory |
POST /api/embed |
Generate embeddings |
GET /dashboard/api/health |
30+ automated health checks |
GET /dashboard/api/traces |
Recent request traces with scoring details |
GET /dashboard/api/recommendations |
Model mix recommendations per node |
GET /dashboard/api/usage |
Per-node, per-model usage statistics |
GET /dashboard/api/settings |
Current fleet configuration |
Source
- ClawHub: ollama-herd
- GitHub: geeks-accelerator/ollama-herd
- PyPI: ollama-herd