manage_memory descriptions: explicit deferral to manage_contact for person info

Even with manage_contact in the retrieved tool set, models were still
defaulting to manage_memory when the user pasted an address + 'save for
<person>'. Both tools were in front of the model and it picked memory.

Tighten both descriptions to steer at decision-time:
- agent_loop.py manage_memory description: clarify scope is facts
  about the USER, with an explicit 'DO NOT use for info about another
  person' + a 'use manage_contact instead' line.
- tool_index.py manage_memory description: same in shorter form, so the
  embedded retrieval signal is consistent with the prompt-time
  description.

src/tool_index.py

@@ -87,7 +87,7 @@ BUILTIN_TOOL_DESCRIPTIONS: Dict[str, str] = {
     "pipeline": "Run a multi-step AI pipeline with multiple models. Chain tasks together in sequence.",
     "list_models": "List all available AI models and their endpoints.",
     "manage_session": "Chat management: rename, archive, delete, or fork chats (the UI calls these 'chats'; internally 'sessions'). Use for 'rename my chats', 'rename this chat', 'archive/delete a chat'.",
-    "manage_memory": "Memory management: list, add, edit, delete, or search persistent memories.",
+    "manage_memory": "Memory management: list, add, edit, delete, or search persistent memories. For facts about the USER (their name, preferences, where they live). NOT for info about ANOTHER person — addresses, phones, emails belonging to a contact go in manage_contact, not memory.",
     "manage_skills": "Skill management: add, update, publish, or search reusable skills/presets.",
     "manage_tasks": "Scheduled task management: list, create, edit, delete, pause, resume, or run cron tasks.",
     "manage_endpoints": "Endpoint management: list, add, delete, enable, or disable model API endpoints.",