Update planning package after Phase 0B

planning/CONTEXT-AND-MEMORY.md

@@ -1,6 +1,6 @@
 # Adventure Storyteller — Context and Memory
 
-**Status:** Draft v0.1  
+**Status:** v1.0 — aligned to Phase 0B findings  
 **Purpose:** Define what information is supplied to the narrator on each turn, how long-term memory works, and how authority, lineage, retrieval, summaries, and imported knowledge interact.
 
 ## 1. Design Goal
@@ -420,7 +420,7 @@ Reason:
 - lexical retrieval is transparent and precise for names/terms,
 - semantic retrieval is useful for conceptually related old events.
 
-Phase 0B should determine what the selected base already supports.
+Phase 0B confirmed useful local semantic memory in AI-DnD and deterministic lexical lore in ai-adventure. The selected production direction is hybrid local retrieval, implemented incrementally with a lexical path that remains usable when semantic embeddings are unavailable.
 
 ## 17. Embeddings
 
@@ -1083,25 +1083,25 @@ If the narrator makes an unexpected choice, the system should support questions
 
 This is why context provenance is a first-class requirement.
 
-## 57. Phase 0B Validation Questions
+## 57. Phase 0B Findings Applied
 
-Codex should answer:
+The selected AI-DnD base was exercised with real local Ollama embeddings and demonstrated useful lineage behavior:
 
-1. How does AI-DnD currently rank and retrieve memories?
-2. Are AI-DnD memories branch-aware?
-3. Can abandoned-branch memories leak into active context?
-4. How are Story Cards selected and injected?
-5. Can Story Cards be generalized into Canon / Reference / Inspiration classes?
-6. What exact embedding provider does local AI-DnD use with Ollama?
-7. Can memory retrieval work fully offline?
-8. What context components are visible in AI-DnD's Insights view?
-9. How does Open Dungeon decide when to summarize old history?
-10. Can ai-adventure's FTS lore layer be retained as a deterministic lexical retrieval component?
-11. How difficult would hybrid lexical + semantic retrieval be in the selected base?
-12. Can current context budgeting preserve hard canon under pressure?
-13. Are summaries tied explicitly to source lineage?
-14. Can memory extraction failure occur without blocking a successful turn?
-15. Can prompt/context snapshots be retained without excessive database growth?
+- branch-scoped memory retrieval worked,
+- a memory from a later/abandoned depth was excluded after moving the active head backward,
+- the same memory became eligible again after Redo/return to the applicable lineage,
+- switching to a different branch prevented abandoned-branch terms from appearing in the assembled prompt,
+- the context/Insights path exposes labeled prompt sections and token costs.
+
+Planning consequences:
+
+1. Preserve AI-DnD's common lineage filtering/chokepoint rather than replacing memory from scratch.
+2. Make summaries explicitly lineage/turn-range anchored; never rely on a positional message watermark.
+3. Keep accepted story memory distinct from heuristic/inferred memory.
+4. Imported knowledge remains a separate subsystem; do not promote Story Cards into the knowledge store merely because they are prompt-injection primitives.
+5. Use local Ollama embeddings for semantic story memory where enabled; retain a lexical/deterministic path for imported knowledge.
+6. Context/state extraction must be tested at realistic prompt length because Phase 0B showed model protocol adherence can degrade under full application context.
+7. Derived memory/summary failure must not corrupt or roll back an otherwise valid authoritative story commit.
 
 ## 58. Acceptance Criteria
 
@@ -1117,6 +1117,8 @@ The final implementation must satisfy:
 - retrieval works locally,
 - no remote embeddings/search are required,
 - abandoned branch memories do not leak,
+- moving the active head backward excludes memories derived after that head,
+- Redo/returning to the valid lineage can make those memories eligible again,
 - context remains bounded,
 - output space is reserved,
 - prompt composition is inspectable,
@@ -1124,7 +1126,7 @@ The final implementation must satisfy:
 - summaries are lineage-safe,
 - memory failures do not corrupt authoritative story state.
 
-## 59. Current Recommendation
+## 59. Selected Context / Memory Design
 
 Use a layered, authority-aware context builder:
 
@@ -1141,13 +1143,13 @@ Use a layered, authority-aware context builder:
                     v
             ----------------
                     +
-            Story Summary
+       Lineage-Anchored Summary
                     +
        Relevant Story Memories
                     +
        Relevant Local Knowledge
                     +
-             Recent History
+       Recent Active-Lineage Turns
                     +
              Current Input
                     |
@@ -1155,14 +1157,14 @@ Use a layered, authority-aware context builder:
                  OLLAMA
 ```
 
-Retrieval should be:
+Retrieval must be:
 
 ```text
 local
-+ lineage-aware
++ lineage-aware where derived from story history
 + provenance-preserving
 + authority-aware
 + token-bounded
 ```
 
-The application should treat context construction as a deterministic subsystem that can be inspected and tested independently of prose generation.
+The application treats context construction as a deterministic, independently testable subsystem. AI-DnD's lineage-aware memory implementation is the starting point; the project's own authority and imported-knowledge rules define the target behavior.