chore(todo): file local-llm and uv install tasks; process inbox

Filed two new [#B] parent tasks. The local offline LLM runtime task carries design-decision and implementation children for resolving the open design questions alongside implementation work. The uv install task matches the existing eask/signal-cli tooling-codification shape — load-bearing for other projects, manually installed today, codify so fresh installs pick it up. Four cross-project handoffs moved to outbox.

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+#+TITLE: Install local offline LLM runtime and model cache
+#+DATE: 2026-05-28
+#+SOURCE_PROJECT: rulesets
+#+REQUEST_TYPE: install-feature
+#+STARTUP: showall
+
+* Request
+
+Please add local offline LLM support to =archsetup='s normal install process so
+machines can run a local coding agent when there is no network.
+
+This came from the =rulesets= generic-agent-runtime design pass. =rulesets=
+should become runtime-neutral, but it needs =archsetup= to provision the local
+model runtime and prefetch model files while network is available.
+
+* Hardware-specific recommendations
+
+** High-end Strix Halo machine
+
+Detected with =inxi=:
+
+- AMD Ryzen AI Max+ 395
+- 128 GiB RAM
+- Radeon 8060S / Strix Halo unified memory
+
+Install:
+
+- Default offline coding model:
+  =Qwen3-Coder-30B-A3B-Instruct-GGUF=, prefer =Q6_K= on this machine.
+- Compatibility quant:
+  =Qwen3-Coder-30B-A3B-Instruct-GGUF Q4_K_M=.
+- Larger general/long-context fallback:
+  =Qwen3-Next-80B-A3B-Instruct-GGUF Q4_K_M=.
+
+** velox
+
+Detected with =ssh velox inxi -C -G -m -S --filter=:
+
+- Intel Core i7-1370P
+- 64 GiB RAM
+- Intel Iris Xe integrated graphics
+
+Install:
+
+- Strongest practical offline coding default:
+  =Qwen3-Coder-30B-A3B-Instruct-GGUF Q4_K_M=.
+- Add an 8B fallback model for quick edits and low-latency triage.
+
+Expect =velox= to be CPU/low-end-iGPU bound. The 30B model fits, but latency
+will be the limiting factor.
+
+* Runtime stack
+
+Recommended packages/components:
+
+- =llama.cpp= with CPU and Vulkan support where practical.
+- Optional =ollama= as a simple model manager/API for workflows that prefer it.
+- A shared local model cache, e.g. =~/.local/share/llm/models= or
+  =/srv/models/llm=.
+- OpenAI-compatible local endpoints:
+  - coding model on =127.0.0.1:8081=
+  - larger/general model on =127.0.0.1:8082= when installed
+  - leave =127.0.0.1:11434= for =ollama= if used
+
+* Install behavior
+
+- Install runtime packages during normal setup.
+- Prefetch model files when network is available.
+- Make model download idempotent: skip if exact file already exists.
+- Do not make the install fail hard if model download is unavailable; surface a
+  clear follow-up saying local offline LLM support is incomplete.
+- Add a smoke test command that starts the local endpoint and asks a short prompt.
+
+* Why this belongs in archsetup
+
+=rulesets= can provide the runtime manifests, launcher behavior, and project
+instructions, but it should not own machine provisioning. =archsetup= already
+owns package installation and per-host setup, so it is the right place to install
+=llama.cpp=/=ollama= and maintain the machine-local model inventory.
+
+* Sources checked
+
+- Qwen3-Coder 30B GGUF quant listings show Q4_K_M around 18.6 GB and Q6_K around
+  25.1 GB.
+- Qwen3-Next 80B GGUF model card shows Q4_K_M around 48.4 GB and native 262K
+  context.
+- =llama.cpp= supports CPU and GPU backends including Vulkan/HIP/ROCm; keep the
+  backend configurable per host.