feat: add Phase F.2 - The Biographer (memory agent)

Add The Biographer household member for user memory management:

Memory Service (direct access layer):
- src/core/memory_service.py for fast, LLM-free lookups
- Profile, preference, and fact management
- Session context with Redis caching
- Steward integration via prefetch_context()

The Biographer Agent:
- src/agents/biographer/ package with PydanticAI agent
- Discreet chronicler personality for privacy
- Tools: recall_semantic, list_memories, store_insight,
  update_profile, update_preference, forget_memory
- Registered with Household Registry on startup

Steward Integration:
- Memory context pre-fetch during analysis
- Profile/preferences included in Butler note
- Keyword-based context determination

Also includes:
- delegate_to_biographer() wrapper
- 34 new tests (capability + memory service)
- Version bump to 1.2.0

Documentation cleanup:
- Removed obsolete PHASE2_COMPLETE.md, PHASE2_PLAN.md
- Removed docs/library-desk-requirements.md
- Moved ORCHESTRATION_SCENARIOS.md to project root

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

src/agents/delegation.py

@@ -146,7 +146,84 @@ async def delegate_to_librarian(
         )
 
 
+async def delegate_to_biographer(
+    task: str,
+    context: str = "",
+) -> DelegationResult:
+    """
+    Delegate a memory task to The Biographer.
+
+    The Biographer handles:
+    - Semantic recall ("What car do I drive?", "What's my job?")
+    - Recording new facts from conversation
+    - Profile updates (name, location, timezone)
+    - Preference updates (units, theme)
+    - Memory management (forget, list)
+
+    For direct key-based lookups (get location, get timezone), use
+    memory_service directly - it's faster and doesn't require LLM.
+
+    Args:
+        task: Clear description of what needs to be done.
+              Include the action verb (recall, remember, forget, etc.)
+              Example: "What car do I drive?"
+              Example: "Remember that I work at Acme Corp"
+        context: Additional context from the user's request or
+                 conversation history
+
+    Returns:
+        DelegationResult with The Biographer's response
+
+    Example:
+        >>> result = await delegate_to_biographer(
+        ...     task="What do you know about my preferences?",
+        ...     context="User is asking about stored information",
+        ... )
+        >>> if result.success:
+        ...     print(result.output)
+    """
+    from src.agents.biographer.agent import run_biographer
+
+    logger.info(
+        "delegation_to_biographer_started",
+        task=task[:100],
+        has_context=bool(context),
+    )
+
+    try:
+        # Use run() not run_stream() - avoids Ollama bug
+        output = await run_biographer(task=task, context=context)
+
+        logger.info(
+            "delegation_to_biographer_completed",
+            task=task[:50],
+            output_length=len(output),
+        )
+
+        return DelegationResult(
+            expert_name="biographer",
+            task=task,
+            success=True,
+            output=output,
+        )
+
+    except Exception as e:
+        logger.error(
+            "delegation_to_biographer_error",
+            task=task[:50],
+            error=str(e),
+            exc_info=True,
+        )
+
+        return DelegationResult(
+            expert_name="biographer",
+            task=task,
+            success=False,
+            output="",
+            error=str(e),
+        )
+
+
 # Future expert delegation wrappers will be added here:
-# - delegate_to_memory(task, context) -> DelegationResult
 # - delegate_to_home_automation(task, context) -> DelegationResult
 # - delegate_to_developer(task, context) -> DelegationResult