Local Llm Troubleshooter

What it does

The Local LLM Troubleshooter is a diagnostic power-tool for developers and AI engineers whose local inference stacks (Ollama, LM Studio, llama.cpp, vLLM, or Hugging Face) are failing. It eliminates the guesswork of "why is my model slow?" or "why won't this load?" by running a bundled diagnostic script that probes connection states, scans logs for failure signatures, and detects stalled downloads.

Why use this skill

Prompting a generic AI about local hardware issues often leads to circular advice. This skill is better because it uses llm_doctor.py to act as a system sensor. It identifies specific technical blockers like GGUF version mismatches, CUDA OOM (Out of Memory) errors, port conflicts, runner crashes, and stalled Hugging Face blobs. It maps these findings to a curated playbook of OS-specific fixes for Apple Silicon, NVIDIA, and WSL2 environments.

Supported tools

• Inference Servers: Ollama, LM Studio, llama.cpp, vLLM
• Model Sources: Hugging Face (hub downloads), Ollama library
• Frameworks: GGUF, local runners, GPU-accelerated backends

What the output looks like

The skill provides a structured triage report including a connectivity verdict (up/down/stuck), identification of the specific bottleneck, and an ordered list of high-probability fixes—ranging from context window adjustments to environment variable corrections.