Neural Network Ops is a specialized management skill for diagnosing, tuning, and routing LLM providers to ensure maximum agent uptime.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install neural-network-diagnostics
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install neural-network-diagnostics using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Neural Network Ops?
Neural Network Ops is designed to maintain the responsiveness and reliability of Openclaw Skills by actively managing model providers and fallback logic. It serves as a technical bridge between the agent and various LLM backends including Groq, OpenRouter, and local Ollama instances, ensuring that communication remains fluid even during provider outages or rate limiting events.
By implementing a robust routing policy and real-time triage protocols, this skill allows developers to automate the selection of stable models based on latency, cost, and availability. It acts as a system administrator for your AI's brain, handling everything from memory management on CPU-bound servers to clearing session deadlocks that cause bot silence.
Neural Network Ops Use Cases
- Resolving silent bot issues in Telegram caused by provider connection failures.
- Automating failover from high-speed cloud providers like Groq to local fallbacks like Ollama.
- Fixing rate limit and timeout errors by adjusting model routing and context window constraints.
- Cleaning up orphaned user messages and session corruption to restore agent responsiveness.
- Monitoring system health and log patterns to preemptively tune model performance.
How Neural Network Ops Works
- The skill performs a fast triage by checking the status of the gateway and backend services like Ollama.
- It analyzes system logs for specific error patterns such as rate limits, context window size issues, or orphaned messages.
- Based on the findings, it applies a prioritized routing policy to select the best available model (e.g., Groq for speed, Ollama for local fallback).
- If bottlenecks are detected, it executes recovery playbooks to restart services or clear session caches.
- It reports the final health status including the active primary model and current fallback chain.
Neural Network Ops Setup
To deploy Neural Network Ops within your Openclaw Skills environment, ensure your system services are accessible and verify your current status with:
systemctl is-active openclaw-gateway ollama
journalctl -u openclaw-gateway -n 40 --no-pager
Configure your local provider settings in your configuration file to ensure stable local fallbacks:
{
"id": "qwen2.5:7b",
"name": "Qwen 2.5 7B (local)",
"contextWindow": 32768,
"maxTokens": 2048
}
Neural Network Ops Data Schema & Taxonomy
Neural Network Ops organizes health data and routing metadata using the following structure:
| Attribute | Description |
|---|---|
| Gateway Status | Current state of the OpenClaw service (active/inactive). |
| Telegram Provider | Connectivity status of the messaging interface. |
| Primary Model | The current top-tier provider and model ID in use. |
| Fallback Chain | An ordered list of backup models used when the primary fails. |
| Findings | A prioritized list of detected technical issues. |
Neural Network Ops Advanced Features
- Multi-provider failover logic across cloud (Groq, OpenRouter) and local (Ollama) backends.
- Automated session purging to resolve persistent 'orphaned user message' loops.
- Pre-warming protocols for local models to reduce latency during fallback triggers.
- Safety guardrails that prevent API key exposure and require confirmation for irreversible actions.
- Specific constraints for local LLM deployment on resource-limited hardware (e.g., RAM-aware routing).
SKILL.md
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