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Ollama — Herd Your LLMs Into One Smart Endpoint
by
Twin Geeks
· GitHub ↗
· v1.0.0
· MIT-0
90
Downloads
2
Stars
0
Active Installs
1
Versions
Install in OpenClaw
/install ollama-fleet-router
Description
Ollama fleet router — herd your Ollama LLMs into one smart endpoint. Route Llama, Qwen, DeepSeek, Phi, Mistral, and Gemma across multiple devices with 7-sign...
Usage Guidance
This skill appears to be a legitimate local Ollama fleet router, but it asks you to pip install a third‑party package and will automatically download models to nodes (auto-pull). Before installing or running: 1) verify the PyPI package and GitHub repo (check publisher, recent commits, issues). 2) Be prepared for large model downloads and disk/VRAM usage; confirm you want auto-pull enabled. 3) Ensure you trust the package source because pip install runs arbitrary code. 4) Note the small manifest mismatch: the runtime needs python/pip and the herd/herd-node binaries, which the registry metadata only lists as optional — make sure those are present. If you need higher assurance, inspect the package source code on the repo or install in an isolated environment first.
Capability Analysis
Type: OpenClaw Skill
Name: ollama-fleet-router
Version: 1.0.0
The skill bundle provides a legitimate utility for load-balancing and routing requests across multiple Ollama LLM instances. It includes clear documentation for installation via 'pip install ollama-herd' and provides specific guardrails in SKILL.md to prevent the AI agent from performing destructive actions (like deleting models or configuration files) without user confirmation. The requested permissions (file access to ~/.fleet-manager/ and network tools like curl/wget) are consistent with the stated purpose of managing a local LLM fleet.
Capability Assessment
Purpose & Capability
The name/description (Ollama fleet router) match the SKILL.md: it tells you to pip install a package, run a router and per-node agent, and route local Ollama instances. Minor mismatch: registry top-level requirements list only curl/wget while the runtime instructions rely on pip/python and the commands 'herd'/'herd-node' (the SKILL metadata lists python3/pip/sqlite3 as optional bins). Requiring a PyPI package and local agents is coherent with the stated purpose, but the dependency on Python/pip is not enforced in the manifest.
Instruction Scope
Instructions remain within the router’s scope (start router, call local endpoints, enable features via dashboard endpoints). They also describe auto-pull (automatic model downloads) and reference config paths (~/.fleet-manager/*). The guardrails state not to modify ~/.fleet-manager without user confirmation. Nothing in SKILL.md instructs reading unrelated system files or exfiltrating secrets, but auto-pull will download large model files and the router will access local model state and logs — which is expected but impactful.
Install Mechanism
No install spec in the manifest, but the runtime instructions require 'pip install ollama-herd' from PyPI. Installing a third‑party PyPI package can execute arbitrary code on the host. That is expected for a Python-based router, but it's a medium-risk install action and the skill does not declare an automated, vetted install; the agent or user would run pip at their discretion.
Credentials
The skill declares no credentials and only needs common networking tools (curl/wget) and optionally python/pip/sqlite3. The listed configPaths (~/.fleet-manager/latency.db and logs) are appropriate for a router that tracks latency and logs. No unrelated secrets or external service tokens are requested.
Persistence & Privilege
always:false and no special persistence or modification of other skills is requested. The guardrails explicitly say not to restart or modify the router/node agents or ~/.fleet-manager without confirmation. Autonomous invocation is allowed (default) but not combined with any elevated privileges in the manifest.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install ollama-fleet-router - After installation, invoke the skill by name or use
/ollama-fleet-router - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Ollama Fleet Router 1.0.0 — Initial Release
- One smart endpoint for routing LLM requests across multiple Ollama devices, with drop-in OpenAI SDK compatibility.
- Advanced fleet scoring: routes requests based on VRAM, model availability, queue depth, latency, and more (7-signal scoring).
- Robust auto-retry, VRAM-aware fallback, and context protection for reliable and efficient operation.
- Supports image generation, speech-to-text, and embeddings, all via the same endpoint.
- Real-time dashboard for monitoring fleet health, usage, models, and workloads.
- Includes project-based request tagging and strict guardrails for safety.
Metadata
Frequently Asked Questions
What is Ollama — Herd Your LLMs Into One Smart Endpoint?
Ollama fleet router — herd your Ollama LLMs into one smart endpoint. Route Llama, Qwen, DeepSeek, Phi, Mistral, and Gemma across multiple devices with 7-sign... It is an AI Agent Skill for Claude Code / OpenClaw, with 90 downloads so far.
How do I install Ollama — Herd Your LLMs Into One Smart Endpoint?
Run "/install ollama-fleet-router" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Ollama — Herd Your LLMs Into One Smart Endpoint free?
Yes, Ollama — Herd Your LLMs Into One Smart Endpoint is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Ollama — Herd Your LLMs Into One Smart Endpoint support?
Ollama — Herd Your LLMs Into One Smart Endpoint is cross-platform and runs anywhere OpenClaw / Claude Code is available (darwin, linux).
Who created Ollama — Herd Your LLMs Into One Smart Endpoint?
It is built and maintained by Twin Geeks (@twinsgeeks); the current version is v1.0.0.
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