Reads the hardware specifications of the local machine: CPU, RAM, motherboard and OS. Returns a structured JSON object.

Provides real-time system performance: CPU load, memory usage, and top processes.

Performs a deep scan for LLM inference optimization: GPU details, real memory bandwidth benchmark, ML runtimes (Ollama, Docker, WSL), and environment variables.

Returns the expert instructions and rules for optimizing LLM inference on this specific hardware. Call this to learn HOW to interpret analyze_inference_config results.

(BETA) Checks if a specific LLM model can run on this machine. Returns optimal quantization and estimated tokens per second. Requires remote API connection.

(BETA) Recommends the best LLM models that can run locally on this machine. Requires remote API connection.

Reports current memory pressure: total/used/free/available memory, swap usage, and top processes by RSS.

Reports per-disk health: type (NVMe/SSD/HDD), vendor, temperature, SMART status, and firmware.

Reports current CPU and GPU thermal and frequency state: temperature, utilization, and fan speed.

Detects running antivirus/EDR products and reads their exclusion rules. Checks dev hot paths coverage.

Monitors system metrics (CPU load, RAM usage, CPU temperature) over a configurable duration (up to 10 minutes) and returns min/max/avg statistics. Use duration_seconds to set the observation window and interval_seconds to control sampling granularity.