total-recallllm-setuplisted

# total-recall LLM + embed setup Runs the operator-facing setup script that installs product ollama (plugin data dir, daemon on `:11435`) and pulls: - refine model (default `qwen3.5:2b`) — chat refinement (provider default `auto`) - embed model (default `qwen3-embedding:0.6b`) — format-v2 hybrid dense recall **`TOTAL_RECALL_EMBED_MODEL` does not need to be set.** Unset is correct — the plugin defaults to `qwen3-embedding:0.6b`. Do not set a HuggingFace id. After setup succeeds and the product daemon is reachable with models present, SessionStart stops emitting the not-ready notice (and will not re-fire once shown once via `.ollama_notice_shown`). Steps: 1. Run `${CLAUDE_PLUGIN_ROOT}/scripts/llm-setup.sh` and stream its output to the operator. The script is idempotent — re-running on a fully-set-up machine is a no-op. Leave `TOTAL_RECALL_EMBED_MODEL` unset unless overriding with another **ollama** tag. 2. When it exits 0, confirm both models are ready and recommend `/total-recall:recall-rebuild` (or `total-recall rebuild --yes`) so the next rebuild picks up LLM refinement **and** dense vectors. 3. **Only if** the operator still has a leftover HuggingFace/fastembed id in env (e.g. `TOTAL_RECALL_EMBED_MODEL=Alibaba-NLP/gte-modernbert-base` from pre-v2), tell them to **unset** it. Fresh installs never need this step. Product MCP config does not pin an embed model. 4. If it exits non-zero, surface the error verbatim and point at `docs/llm-refinemen