Add Cold Wake story lab experiment

notes/fresh-workspace-handoff.md

@@ -48,6 +48,13 @@ Ghostlight now has the persistence spine plus the first architecture payload:
   - `examples/lore-grounding/historical-flashpoint.template.json`
   - `examples/lore-grounding/cold-wake-panic.ganymede-corridor.json`
   - `tools/validate_lore_grounding.py`
+- Cold Wake story-lab seam:
+  - `docs/experiments/cold-wake-story-lab.md`
+  - `examples/agent-state.cold-wake-story-lab.json`
+  - `examples/projections/cold-wake-story-lab.jsonl`
+  - `examples/projections/cold-wake-story-lab.pretty.json`
+  - `experiments/cold-wake-story-lab/scene-03-maer-veyr.qwen3-5-9b.capture.json`
+  - `tools/build_cold_wake_story_lab_fixture.py`
 - Cold Wake fixture note:
   - `docs/architecture/aetheria-cold-wake-training-fixture.md`
 - first projection example seam:
@@ -76,8 +83,9 @@ training feedstock for projection and dialogue scaffolding.
 
 ## Current Next Action
 
-Choose one room inside the Cold Wake Panic and build the first grounded
-projection fixture from the Ganymede corridor digest.
+Tighten the Cold Wake story-lab projection prompt around unresolved personhood
+suspicion, then run the next response turn through Qwen and keep accepted or
+rejected outputs as training data.
 
 Cat/Oz remains useful as an Elysium procedural mechanics fixture, but grounded
 training data should start from authored historical lore rather than gameplay
@@ -99,11 +107,17 @@ Completed projection path items:
 - choose Cold Wake Panic as the first authored historical flashpoint
 - fill the first draft lore grounding digest:
   `examples/lore-grounding/cold-wake-panic.ganymede-corridor.json`
+- define the Cold Wake story lab as a four-scene arc with Maer Tidecall as
+  protagonist
+- add the first Cold Wake projection example and first Qwen response capture
+- widen projection from dialogue-only turns to response turns that can include
+  action, silence, withdrawal, violence, or mixed beats
 
 Remaining projection path:
 
-- choose the first Cold Wake room for a grounded projection fixture
-- create speaker-local projection examples from the Cold Wake digest
+- revise the first Maer/Veyr projection so unresolved personhood suspicion stays
+  unresolved in Qwen output
+- run additional story-lab response turns through Qwen
 - build a deterministic speaker-local input slicer
 - use a frontier teacher model to generate/audit projection artifacts
 - train a smaller student projector only after the artifact schema, input

notes/ghostlight-current-system-map.md

@@ -45,6 +45,9 @@ state and re-entry discipline.
 - `docs/architecture/projection-distillation-plan.md`
   - plan for using a frontier teacher model to generate reviewed projection
     artifacts before training a smaller student projector
+- `docs/experiments/cold-wake-story-lab.md`
+  - four-scene Cold Wake writing experiment using Ghostlight projection as a
+    story-generation crutch and training-data source
 - `docs/architecture/schema-future-mechanisms.md`
   - parking lot for appraisal, transition, belief, action, conversation,
     resource, dyad, institution, memory, and embodiment mechanisms not yet
@@ -72,10 +75,16 @@ state and re-entry discipline.
     stance
 - `examples/agent-state.call-of-the-void.json`
   - first Call of the Void-flavored fixture for schema and projection work
+- `examples/agent-state.cold-wake-story-lab.json`
+  - first story-shaped historical fixture for Cold Wake projection work
 - `examples/projections/call-of-the-void.scene-broken-taxi-oz.jsonl`
   - first reviewed Cat and Oz projection examples
 - `examples/projections/call-of-the-void.scene-broken-taxi-oz.pretty.json`
   - pretty-printed mirror for inspecting the first projection examples
+- `examples/projections/cold-wake-story-lab.jsonl`
+  - first response-turn projection example for the Cold Wake story lab
+- `experiments/cold-wake-story-lab/`
+  - Qwen response captures and reviews from the writing experiment
 - `examples/lore-grounding/historical-flashpoint.template.json`
   - fillable template for the first historical Aetheria grounding digest
 - `examples/lore-grounding/cold-wake-panic.ganymede-corridor.json`
@@ -91,6 +100,8 @@ state and re-entry discipline.
   - dependency-free validator for projection example JSONL records
 - `tools/validate_lore_grounding.py`
   - dependency-free validator for lore grounding digest examples
+- `tools/build_cold_wake_story_lab_fixture.py`
+  - generator for the verbose Cold Wake story-lab state fixture
 
 ## What Does Not Exist Yet
 
@@ -103,7 +114,9 @@ state and re-entry discipline.
 - a relationship engine
 - a culture prior engine
 
-The canonical agent-state schema, first projection example schema, lore
-grounding digest schema, and first draft Cold Wake grounding digest now exist as
-v0 seams. The next implementation target is choosing one Cold Wake room for a
-grounded projection fixture, followed by the deterministic input slicer.
+The canonical agent-state schema, projection example schema, lore grounding
+digest schema, first draft Cold Wake grounding digest, and first Cold Wake
+story-lab Qwen capture now exist as v0 seams. The next implementation target is
+tightening the first Maer/Veyr projection around unresolved personhood suspicion,
+then running the next response turn through Qwen before building the
+deterministic input slicer.

notes/ghostlight-implementation-plan.md

@@ -51,6 +51,12 @@
      the first draft historical grounding digest.
    - Build the first grounded projection fixture from one specific Cold Wake
      room rather than from the whole crisis at once.
+   - Use `docs/experiments/cold-wake-story-lab.md` and
+     `examples/agent-state.cold-wake-story-lab.json` as the first story-shaped
+     writing lab.
+   - Treat projection outputs as response turns, not dialogue-only turns:
+     characters may speak, act, withdraw, stay silent, use violence, or combine
+     speech and action when state and scene pressure justify it.
    - Use a frontier teacher model to produce reviewed projection artifacts from
      structured state and lore grounding digests.
    - Save accepted and rejected projection examples as supervised data.