docs: split CLAUDE.md into path-scoped .claude/rules; fix dev/test commands

- CLAUDE.md trimmed to whole-repo facts (58 lines); subsystem guidance
  moved to .claude/rules/{startos-package,fastapi-image,redaction,
  audio-speech}.md with paths: frontmatter so each loads only when
  matching files are touched
- .gitignore: track .claude/rules/ while keeping the rest of .claude/
  (settings.local.json) ignored
- test-audio-with-speakers.sh: require audio-file arg in docs, replace
  owner-specific SPARK_CONTROL/VLLM defaults with generic ones
  (localhost dev server + Spark Control vLLM proxy), discover the
  loaded LLM via /api/status since /v1/models lists audio models only
- document REDACTION_MAP_DB + CONNECTIVITY_LOG as required for local
  dev (/data only exists in the container)
- prettier pass over startos/actions (formatting drift)

scripts/test-audio-with-speakers.sh

@@ -9,6 +9,13 @@
 # Usage:
 #   bash scripts/test-audio-with-speakers.sh <audio-file> [--people "Name1, Name2"]
 #
+# Env:
+#   SPARK_CONTROL — base URL of a running Spark Control instance
+#                   (default http://127.0.0.1:9999, i.e. a local dev server;
+#                   point it at your installed package URL otherwise)
+#   VLLM          — /v1 base URL used for chat/completions
+#                   (default $SPARK_CONTROL/v1 — Spark Control proxies vLLM)
+#
 # Examples:
 #   # No participants list (LLM will only resolve speakers it can verify from audio cues)
 #   bash scripts/test-audio-with-speakers.sh ~/Library/Application\ Support/hyprnote/sessions/*/audio.mp3
@@ -33,8 +40,8 @@ if [ ! -f "$AUDIO" ]; then
   exit 1
 fi
 
-SPARK_CONTROL="${SPARK_CONTROL:-https://spark.satsflows.com}"
-VLLM="${VLLM:-http://<spark-1-ip>:8888/v1}"
+SPARK_CONTROL="${SPARK_CONTROL:-http://127.0.0.1:9999}"
+VLLM="${VLLM:-$SPARK_CONTROL/v1}"
 
 echo "════════════════════════════════════════════════════════════════"
 echo "Audio:           $AUDIO ($(du -h "$AUDIO" | cut -f1))"
@@ -86,7 +93,9 @@ head -3 /tmp/transcript-formatted.txt | sed 's/^/    /'
 # ───────── Stage 3: discover current LLM ─────────
 echo
 echo "▶ Stage 3: discover current vLLM model..."
-MODEL=$(curl -sS $VLLM/models | python3 -c "import json,sys; print(json.load(sys.stdin)['data'][0]['id'])")
+# Note: Spark Control's /v1/models lists *audio* models (STT + TTS voices),
+# not the LLM — ask /api/status for the currently loaded vLLM model instead.
+MODEL=$(curl -sSk "$SPARK_CONTROL/api/status" | python3 -c "import json,sys; print(json.load(sys.stdin)['vllm']['current_model'])")
 echo "  Model: $MODEL"
 
 # ───────── Stage 4: build LLM request ─────────