feat: add Honcho AI-native memory integration

Opt-in persistent cross-session user modeling via Honcho. Reads
~/.honcho/config.json as single source of truth (shared with
Claude Code, Cursor, and other Honcho-enabled tools). Zero impact
when disabled or unconfigured.

- honcho_integration/ package (client, session manager, peer resolution)
- Host-based config resolution matching claude-honcho/cursor-honcho pattern
- Prefetch user context into system prompt per conversation turn
- Sync user/assistant messages to Honcho after each exchange
- query_user_context tool for mid-conversation dialectic reasoning
- Gated activation: requires ~/.honcho/config.json with enabled=true

tools/honcho_tools.py

@@ -0,0 +1,102 @@
+"""Honcho tool for querying user context via dialectic reasoning.
+
+Registers ``query_user_context`` -- an LLM-callable tool that asks Honcho
+about the current user's history, preferences, goals, and communication
+style. The session key is injected at runtime by the agent loop via
+``set_session_context()``.
+"""
+
+import json
+import logging
+
+logger = logging.getLogger(__name__)
+
+# ── Module-level state (injected by AIAgent at init time) ──
+
+_session_manager = None  # HonchoSessionManager instance
+_session_key: str | None = None  # Current session key (e.g., "telegram:123456")
+
+
+def set_session_context(session_manager, session_key: str) -> None:
+    """Register the active Honcho session manager and key.
+
+    Called by AIAgent.__init__ when Honcho is enabled.
+    """
+    global _session_manager, _session_key
+    _session_manager = session_manager
+    _session_key = session_key
+
+
+def clear_session_context() -> None:
+    """Clear session context (for testing or shutdown)."""
+    global _session_manager, _session_key
+    _session_manager = None
+    _session_key = None
+
+
+# ── Tool schema ──
+
+HONCHO_TOOL_SCHEMA = {
+    "name": "query_user_context",
+    "description": (
+        "Query Honcho to retrieve relevant context about the user based on their "
+        "history and preferences. Use this when you need to understand the user's "
+        "background, preferences, past interactions, or goals. This helps you "
+        "personalize your responses and provide more relevant assistance."
+    ),
+    "parameters": {
+        "type": "object",
+        "properties": {
+            "query": {
+                "type": "string",
+                "description": (
+                    "A natural language question about the user. Examples: "
+                    "'What are this user's main goals?', "
+                    "'What communication style does this user prefer?', "
+                    "'What topics has this user discussed recently?', "
+                    "'What is this user's technical expertise level?'"
+                ),
+            }
+        },
+        "required": ["query"],
+    },
+}
+
+
+# ── Tool handler ──
+
+def _handle_query_user_context(args: dict, **kw) -> str:
+    """Execute the Honcho context query."""
+    query = args.get("query", "")
+    if not query:
+        return json.dumps({"error": "Missing required parameter: query"})
+
+    if not _session_manager or not _session_key:
+        return json.dumps({"error": "Honcho is not active for this session."})
+
+    try:
+        result = _session_manager.get_user_context(_session_key, query)
+        return json.dumps({"result": result})
+    except Exception as e:
+        logger.error("Error querying Honcho user context: %s", e)
+        return json.dumps({"error": f"Failed to query user context: {e}"})
+
+
+# ── Availability check ──
+
+def _check_honcho_available() -> bool:
+    """Tool is only available when Honcho is active."""
+    return _session_manager is not None and _session_key is not None
+
+
+# ── Registration ──
+
+from tools.registry import registry
+
+registry.register(
+    name="query_user_context",
+    toolset="honcho",
+    schema=HONCHO_TOOL_SCHEMA,
+    handler=_handle_query_user_context,
+    check_fn=_check_honcho_available,
+)