feat(briefing): agentic slot injections + persist tool-call receipts

PR 1.5 + PR 2 of the agentic briefing rollout. Extends the agentic
path to cover the morning/midday/afternoon check-in slots in addition
to the 4am compilation, and persists the full tool-call sequence
into the briefing conversation so chat follow-ups see the receipts.

run_slot_injection now honors the briefing_mode setting the same way
run_compilation does: agentic mode routes through run_agentic_briefing
with a check-in system prompt variant, legacy falls back automatically
if the new path returns empty. Signature changed from str to
(str, dict) to surface the agentic message list to the caller.

_agentic_system_prompt now takes the user's local-day window and
timezone, pre-computed by run_agentic_briefing, and embeds them in
the prompt. This eliminates a whole class of "wrong day" bugs that
would otherwise happen when the model tried to translate "today" into
ISO 8601 ranges without knowing the user's timezone.

briefing_scheduler._run_slot_for_user now calls _persist_agentic_messages
after each slot, which walks the agentic message list and stores
every intermediate assistant turn (with its tool calls and results
folded into the flat storage format the existing chat loader expects)
as a real message row. The synthetic "[Midday briefing update]"
user-role messages are no longer created — final prose is written
with metadata.briefing_slot so the UI can still identify it as a
scheduled entry. The agentic user-trigger ("Generate my morning
briefing…") is deliberately skipped so it doesn't recreate the same
fake-user-message problem we're trying to remove.

briefing_conversations.post_message now accepts tool_calls, matching
the schema the Message model already supports. This lets scheduled
briefings write structured tool-use history without reaching into
the model layer.

Net effect with briefing_mode="agentic" on:
- All four slots are grounded in tool results, no more hallucinated
  events or tasks
- Chat follow-ups in the briefing conversation see morning's
  list_events → [] receipt (and everything else), so "what meeting?"
  gets an honest "nothing on the calendar" reply grounded in data
- No more fake [Briefing update] user messages in the chat scroll

Still to come (PR 3): UI polish — tool-call status row, inline cards
for list_events/list_tasks results, visual treatment for slot messages.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

src/fabledassistant/services/briefing_pipeline.py

@@ -461,13 +461,35 @@ _BRIEFING_AGENT_MAX_ROUNDS = 8
 _BRIEFING_AGENT_NUM_CTX = 8192
 
 
-def _agentic_system_prompt(profile_body: str, slot: str) -> str:
+def _agentic_system_prompt(
+    profile_body: str,
+    slot: str,
+    today_iso: str,
+    tz_name: str,
+    day_from_iso: str,
+    day_to_iso: str,
+) -> str:
     """System prompt for the agentic briefing path.
 
     Pushes the model to ground every factual claim in a tool result and
     to be honest when tools return nothing, rather than fabricating
     content to fill the narrative.
+
+    Pre-computes today's window in the user's local timezone so the
+    model can call date-sensitive tools (list_events, list_tasks filters)
+    without having to do any timezone math itself — eliminating a whole
+    class of "wrong day" bugs.
     """
+    tz_block = (
+        f"Today is {today_iso} ({tz_name}). "
+        f"When calling list_events for today, use:\n"
+        f"  date_from = {day_from_iso}\n"
+        f"  date_to   = {day_to_iso}\n"
+        f"These are already the correct local-day boundaries — do not convert "
+        f"them to UTC or any other timezone. For other date ranges, compute in "
+        f"the same timezone.\n\n"
+    )
+
     if slot == "compilation":
         base = (
             "You are the user's personal assistant giving their full morning briefing. "
@@ -505,6 +527,7 @@ def _agentic_system_prompt(profile_body: str, slot: str) -> str:
             "- 3 to 5 sentences, natural prose, no markdown.\n\n"
         )
 
+    base = tz_block + base
     if profile_body:
         base += f"User profile (tone and preferences):\n{profile_body}\n"
     return base
@@ -551,7 +574,6 @@ async def run_agentic_briefing(
     from fabledassistant.services.tools import execute_tool
     from fabledassistant.services.briefing_tools import get_briefing_tools
     from fabledassistant.services.user_profile import build_profile_context
-    from datetime import date as _date
 
     profile_context = await build_profile_context(user_id)
     tools = await get_briefing_tools(user_id)
@@ -563,10 +585,28 @@ async def run_agentic_briefing(
         )
         return "", []
 
-    date_str = _date.today().isoformat()
+    # Compute today's window in the user's local timezone so the model
+    # receives ready-to-use ISO 8601 boundaries and never has to do its
+    # own tz math when calling date-sensitive tools like list_events.
+    tz_name = await get_setting(user_id, "user_timezone") or "UTC"
+    try:
+        user_tz = ZoneInfo(tz_name)
+    except ZoneInfoNotFoundError:
+        user_tz = ZoneInfo("UTC")
+        tz_name = "UTC"
+    now_local = datetime.now(user_tz)
+    today_iso = now_local.date().isoformat()
+    day_start = datetime(now_local.year, now_local.month, now_local.day, 0, 0, 0, tzinfo=user_tz)
+    day_end = datetime(now_local.year, now_local.month, now_local.day, 23, 59, 59, tzinfo=user_tz)
+    day_from_iso = day_start.isoformat()
+    day_to_iso = day_end.isoformat()
+
+    system_prompt = _agentic_system_prompt(
+        profile_context, slot, today_iso, tz_name, day_from_iso, day_to_iso,
+    )
     messages: list[dict] = [
-        {"role": "system", "content": _agentic_system_prompt(profile_context, slot)},
-        {"role": "user", "content": _agentic_user_trigger(slot, date_str)},
+        {"role": "system", "content": system_prompt},
+        {"role": "user", "content": _agentic_user_trigger(slot, today_iso)},
     ]
 
     final_text = ""
@@ -1040,27 +1080,58 @@ async def run_compilation(
     return briefing_text, metadata
 
 
-async def run_slot_injection(user_id: int, slot: str, model: str | None = None) -> str:
+async def run_slot_injection(
+    user_id: int,
+    slot: str,
+    model: str | None = None,
+) -> tuple[str, dict]:
     """
-    Lighter update for 8am/12pm/4pm — gathers fresh data and produces a slot-specific
-    update prompt. Returns the text to inject as a new user→assistant exchange.
+    Lighter update for 8am/12pm/4pm — generates a slot-specific check-in.
+
+    Honors the ``briefing_mode`` setting just like ``run_compilation``:
+    agentic mode routes through the tool-use loop, legacy mode runs the
+    one-shot synthesis path. Falls back to legacy automatically if
+    agentic returns empty.
+
+    Returns ``(text, metadata)`` where metadata may contain
+    ``agentic_messages`` (the full tool-call sequence) if the agentic
+    path was used.
     """
     if model is None:
         model = await get_setting(user_id, "default_model", Config.OLLAMA_MODEL)
 
-    internal_data, external_data, temp_unit = await asyncio.gather(
-        _gather_internal(user_id),
-        _gather_external(user_id),
-        _get_temp_unit(user_id),
-    )
+    briefing_mode = await get_setting(user_id, "briefing_mode", "legacy")
+    agentic_messages: list[dict] = []
+    text = ""
 
-    system = (
-        f"You are a personal assistant giving a brief {slot} check-in. "
-        "The user already had their morning briefing — focus only on what's changed or newly relevant. "
-        "Speak naturally in 2-3 sentences, no markdown formatting, no headers or bullet points."
-    )
-    return await _llm_synthesise(
-        system,
-        _unified_user_prompt(internal_data, external_data, slot, temp_unit),
-        model,
-    )
+    if briefing_mode == "agentic":
+        text, agentic_messages = await run_agentic_briefing(
+            user_id, slot, model, conv_id=None,
+        )
+        if not text:
+            logger.warning(
+                "Agentic slot injection returned empty for user %d slot %s — falling back to legacy",
+                user_id, slot,
+            )
+
+    if not text:
+        internal_data, external_data, temp_unit = await asyncio.gather(
+            _gather_internal(user_id),
+            _gather_external(user_id),
+            _get_temp_unit(user_id),
+        )
+        system = (
+            f"You are a personal assistant giving a brief {slot} check-in. "
+            "The user already had their morning briefing — focus only on what's changed or newly relevant. "
+            "Speak naturally in 2-3 sentences, no markdown formatting, no headers or bullet points."
+        )
+        text = await _llm_synthesise(
+            system,
+            _unified_user_prompt(internal_data, external_data, slot, temp_unit),
+            model,
+        )
+
+    metadata: dict = {}
+    if agentic_messages:
+        metadata["agentic_messages"] = agentic_messages
+    return text, metadata