Initial commit: Howl M365 email management daemon

Full implementation of the Howl email triage system:
- Microsoft Graph API integration with MSAL auth (client-credentials and delegated modes)
- Claude LLM classification via tool use for structured output
- PostgreSQL database with customers, vendors, whitelist, and email_log tables
- Alembic migration for full schema
- APScheduler daemon with graceful shutdown
- Typer CLI (run, dry-run, status commands)
- Business rule classifier with overrides (whitelist protection, low-confidence fallback)
- Action executor (move to folders, flag, escalate with webhook)
- 35 passing unit tests
- README, SETUP, and NEXT_STEPS documentation

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

tests/test_classifier.py

@@ -0,0 +1,91 @@
+from __future__ import annotations
+
+import pytest
+
+from howl.db.queries import SenderMatch
+from howl.llm.schemas import EmailClassification
+from howl.pipeline import classifier
+
+
+def make_classification(**kwargs) -> EmailClassification:
+    defaults = {
+        "classification": "customer_inquiry",
+        "confidence": 0.90,
+        "action": "move_customer",
+        "reasoning": "Test classification",
+        "priority": "normal",
+        "requires_human_review": False,
+        "tags": [],
+    }
+    defaults.update(kwargs)
+    return EmailClassification.model_validate(defaults)
+
+
+def test_whitelist_sender_not_moved_to_spam(settings, whitelist_match):
+    classification = make_classification(action="move_spam", confidence=0.85)
+    final_action, overridden = classifier.decide(whitelist_match, classification, settings)
+    assert final_action == "inbox_keep"
+    assert overridden is True
+
+
+def test_customer_sender_not_moved_to_spam(settings, customer_match):
+    classification = make_classification(action="move_spam", confidence=0.85)
+    final_action, overridden = classifier.decide(customer_match, classification, settings)
+    assert final_action == "move_review"
+    assert overridden is True
+
+
+def test_requires_human_review_forces_move_review(settings, unknown_match):
+    classification = make_classification(
+        action="inbox_keep",
+        confidence=0.75,
+        requires_human_review=True,
+    )
+    final_action, overridden = classifier.decide(unknown_match, classification, settings)
+    assert final_action == "move_review"
+    assert overridden is True
+
+
+def test_low_confidence_falls_back_to_inbox_keep(settings, unknown_match):
+    # Settings has llm_confidence_threshold=0.60, this is 0.45
+    classification = make_classification(
+        action="move_spam",
+        confidence=0.45,
+        requires_human_review=False,
+    )
+    final_action, overridden = classifier.decide(unknown_match, classification, settings)
+    assert final_action == "inbox_keep"
+    assert overridden is True
+
+
+def test_high_confidence_customer_passes_through(settings, customer_match):
+    classification = make_classification(
+        action="move_customer",
+        confidence=0.95,
+        requires_human_review=False,
+    )
+    final_action, overridden = classifier.decide(customer_match, classification, settings)
+    assert final_action == "move_customer"
+    assert overridden is False
+
+
+def test_escalate_not_overridden_by_low_confidence(settings, customer_match):
+    """Escalate action should survive even low confidence — it's already going to human review."""
+    classification = make_classification(
+        action="escalate",
+        confidence=0.40,
+        requires_human_review=True,
+    )
+    final_action, overridden = classifier.decide(customer_match, classification, settings)
+    assert final_action == "escalate"
+
+
+def test_flag_follow_up_survives_requires_human_review(settings, unknown_match):
+    """flag_follow_up is an acceptable requires_human_review action — should not be overridden."""
+    classification = make_classification(
+        action="flag_follow_up",
+        confidence=0.80,
+        requires_human_review=True,
+    )
+    final_action, overridden = classifier.decide(unknown_match, classification, settings)
+    assert final_action == "flag_follow_up"