hal0

Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community detection, and query/path/explain tools.

Use for any question about a codebase, its architecture, file relationships, or project content — especially when graphify-out/ exists, where the question should be treated as a graphify query first. Turns any input (code, docs, papers, images, videos) into a persistent knowledge graph with god nodes, community detection, and query/path/explain tools.

Operating and troubleshooting hal0-managed user-level systemd services. Use when a hal0 platform service (hermes-gateway, hal0-agent@*, etc.) is misbehaving — missing env vars, not starting, not connecting to Telegram/Discord, etc. Encodes the structural fact that hal0 provisioners write secrets files but do NOT wire service units to load them.

The weekly judgment pass over benchlab's benchmark dataset.

Creating ROCmFPX-family quants (ROCmFP3/4/6/8, straight or agent) from BF16/F16 GGUF sources on hal0 / Strix Halo, using the Hal0ai/Hal0_ROCmFPX runner. Use when asked to quantize a model to ROCmFP4 (or FP3/FP6/FP8), build the ROCmFPX llama.cpp tree for a GPU arch, or produce an agent-coherent quant for tool-calling / JSON / coding workloads. Encodes the clone→build→quantize contract and the straight-vs-agent tensor-routing choice.

Running LLM inference benchmarks on hal0 / Strix Halo. Use when asked to benchmark a model, measure tokens/sec (prompt-processing or generation), compare the ROCm vs Vulkan backends, sweep context lengths, or refresh benchmark data. Encodes the structural fact that benchmarking is a rootful GPU op the unprivileged agent reaches ONLY through the hal0-benchctl sudo seam, and that the single iGPU is shared with the live inference slots.

Tuning LLM inference settings on hal0 / Strix Halo for throughput, latency, or memory. Use when asked to optimize/tune a model's llama.cpp flags & values (batch, ubatch, ngl, flash-attn, KV-cache quant, threads), find the fastest config, or close a gap vs other people's numbers. Combines benchmark-driven sweeps (via hal0-bench) with external research (r/LocalLLaMA, llama.cpp GitHub issues/PRs, the kyuz0 toolbox repo). Core rule: never apply a community claim without measuring it locally first.