feat(evaluation): memoir readiness, judge/replay updates, eval web playground

Add memoir_readiness_service and router tests; extend judge schemas/services, replay_service, and conversation rubric; align story route agent, payload, prompts, and story_pipeline_sync; update agent logging, config, and DI. Document internal-eval; add replayDraft util and PlaygroundPage changes in app-eval-web.

api/app/features/memoir/story_pipeline_sync.py

@@ -27,9 +27,11 @@ from app.agents.stage_constants import (
     STAGE_TO_ORDER,
 )
 from app.agents.memoir.story_route_agent import (
+    APPEND_FIRST_CHAPTER_CATEGORIES,
     PLAN_BATCH_MAX_SEGMENTS,
     StoryBatchPlan,
     StoryRouteAgent,
+    default_append_target_story_id,
 )
 from app.agents.state_schema import MemoirStateSchema
 from app.core.config import settings
@@ -530,6 +532,8 @@ def _run_batch_plan_writes(
     user_birth_year: int | None,
     llm: Any,
     narrative_agent: NarrativeAgent,
+    candidate_stories: list,
+    story_meta: dict[str, dict[str, int]],
     background_voice: str = "default",
     occupation: str = "",
     memoir_correlation_id: str | None = None,
@@ -573,6 +577,33 @@ def _run_batch_plan_writes(
                 else:
                     target_story_id = st.id
                     existing_for_narrative = canon
+        elif (
+            unit.decision == "new_story"
+            and chapter_category in APPEND_FIRST_CHAPTER_CATEGORIES
+            and candidate_stories
+            and len(ut_norm)
+            <= int(settings.memoir_story_route_append_guardrail_oral_chars)
+        ):
+            tid_g = default_append_target_story_id(
+                candidate_stories, story_meta, settings
+            )
+            if tid_g:
+                st = session.get(Story, tid_g)
+                if st and st.user_id == user_id:
+                    canon = (st.canonical_markdown or "").strip()
+                    vc = count_story_versions_sync(session, str(st.id))
+                    if len(canon) <= max_chars and vc < max_ver:
+                        target_story_id = st.id
+                        existing_for_narrative = canon
+                        decision_source = "append_guardrail_short_oral"
+                        logger.info(
+                            "event=story_route_append_guardrail memoir_correlation_id={} "
+                            "chapter_category={} oral_len={} story_id={}",
+                            memoir_correlation_id or "",
+                            chapter_category,
+                            len(ut_norm),
+                            tid_g,
+                        )
 
         raw_gen = narrative_agent.generate_narrative(
             stage=chapter_category,
@@ -663,12 +694,13 @@ def _run_batch_plan_writes(
         elapsed = time.perf_counter() - t0
         logger.info(
             "event=story_generated memoir_correlation_id={} route_type=batch "
-            "decision_source={} route_decision={} "
+            "decision_source={} route_decision={} route_planned={} "
             "unit_segments={} used_evidence={} narrative_json_valid={} fidelity_passed={} "
             "fallback_type={} oral_len={} md_len={} chapter_category={} is_append={} "
             "story_id={} seconds={:.3f} oral_normalize_changed={}",
             memoir_correlation_id or "",
             decision_source,
+            "append_story" if is_append else "new_story",
             unit.decision,
             len(unit.segment_ids),
             bool(evidence_text.strip()),
@@ -839,6 +871,8 @@ def run_story_pipeline_for_category_batch(
             user_birth_year=user_birth_year,
             llm=llm,
             narrative_agent=narrative_agent,
+            candidate_stories=candidates,
+            story_meta=story_meta,
             background_voice=background_voice,
             occupation=occupation,
             memoir_correlation_id=memoir_correlation_id,
@@ -879,6 +913,31 @@ def run_story_pipeline_for_category_batch(
                 else:
                     target_story_id = st.id
                     existing_for_narrative = canon
+        elif (
+            route.decision == "new_story"
+            and chapter_category in APPEND_FIRST_CHAPTER_CATEGORIES
+            and candidates
+            and len(om_norm)
+            <= int(settings.memoir_story_route_append_guardrail_oral_chars)
+        ):
+            tid_g = default_append_target_story_id(candidates, story_meta, settings)
+            if tid_g:
+                st = session.get(Story, tid_g)
+                if st and st.user_id == user_id:
+                    canon = (st.canonical_markdown or "").strip()
+                    vc = count_story_versions_sync(session, str(st.id))
+                    if len(canon) <= max_chars and vc < max_ver:
+                        target_story_id = st.id
+                        existing_for_narrative = canon
+                        decision_source = "append_guardrail_short_oral"
+                        logger.info(
+                            "event=story_route_append_guardrail memoir_correlation_id={} "
+                            "chapter_category={} oral_len={} story_id={} route_type=single",
+                            memoir_correlation_id or "",
+                            chapter_category,
+                            len(om_norm),
+                            tid_g,
+                        )
 
         raw_gen = narrative_agent.generate_narrative(
             stage=chapter_category,