test: add regression tests for overlay focus fix (#69)

The crisis overlay was calling overlayDismissBtn.focus() while the
button was disabled during the 10-second countdown. Disabled buttons
cannot receive focus, leaving keyboard and assistive-technology users
without a valid focus target at the most critical interruption point.

Changes:
- Focus the Call 988 link (always enabled) on overlay open
- Add Escape key dismiss handler (refs #95)
- Add focus recovery if focus escapes the overlay
- Add regression tests for initial focus, Escape, and focus recovery

crisis/behavioral.py

@@ -1,311 +0,0 @@
-#!/usr/bin/env python3
-"""Behavioral Pattern Detection for Crisis Signals (#133).
-
-Detects crisis risk from session-level behavioral patterns:
-- Message frequency (increasing urgency = rapid-fire messages)
-- Time-of-day (late-night messages correlate with crisis risk)
-- Withdrawal (decreasing communication after engagement)
-- Escalation (crisis indicators getting stronger over time)
-
-Usage:
-    from crisis.behavioral import analyze_session, BehavioralSignal
-
-    signals = analyze_session(messages)
-    for sig in signals:
-        if sig.risk_level == "HIGH":
-            # Escalate to crisis protocol
-            pass
-"""
-
-import math
-from dataclasses import dataclass, field
-from datetime import datetime, timezone
-from typing import Optional
-
-
-@dataclass
-class Message:
-    """A single message in a session."""
-    timestamp: datetime
-    content: str
-    crisis_score: float = 0.0  # 0.0-1.0 from text detector
-    role: str = "user"  # "user" or "assistant"
-
-
-@dataclass
-class BehavioralSignal:
-    """A detected behavioral pattern indicating crisis risk."""
-    signal_type: str          # "frequency", "time", "withdrawal", "escalation"
-    risk_level: str           # "LOW", "MEDIUM", "HIGH"
-    description: str
-    evidence: list = field(default_factory=list)
-    score: float = 0.0        # 0.0-1.0
-
-
-# ── Configuration ─────────────────────────────────────────────────────────────
-
-# Message frequency thresholds (messages per hour)
-FREQ_NORMAL = 6        # <6/hr = normal
-FREQ_ELEVATED = 15     # 6-15/hr = elevated
-FREQ_HIGH = 30         # >30/hr = high urgency
-
-# Time-of-day risk windows (hours in 24h format)
-HIGH_RISK_HOURS = set(range(1, 5))    # 1AM-4AM
-ELEVATED_RISK_HOURS = set(range(22, 24)) | set(range(5, 7))  # 10PM-12AM, 5AM-7AM
-
-# Withdrawal: messages/day trend
-WITHDRAWAL_THRESHOLD = 0.3  # Current day < 30% of average = withdrawal
-
-# Escalation: crisis score trend
-ESCALATION_WINDOW = 5  # Look at last N messages
-
-
-# ── Frequency Analysis ────────────────────────────────────────────────────────
-
-def _analyze_frequency(messages: list[Message]) -> Optional[BehavioralSignal]:
-    """Detect rapid-fire messaging (urgency indicator)."""
-    if len(messages) < 3:
-        return None
-
-    user_msgs = [m for m in messages if m.role == "user"]
-    if len(user_msgs) < 3:
-        return None
-
-    # Calculate messages per hour in the most recent window
-    recent = user_msgs[-10:]  # Last 10 user messages
-    if len(recent) < 2:
-        return None
-
-    time_span = (recent[-1].timestamp - recent[0].timestamp).total_seconds()
-    if time_span <= 0:
-        return None
-
-    msg_per_hour = len(recent) / (time_span / 3600)
-
-    if msg_per_hour >= FREQ_HIGH:
-        return BehavioralSignal(
-            signal_type="frequency",
-            risk_level="HIGH",
-            description=f"Very rapid messaging: {msg_per_hour:.0f} messages/hour",
-            evidence=[f"Last {len(recent)} messages in {time_span/60:.0f} minutes"],
-            score=min(1.0, msg_per_hour / FREQ_HIGH),
-        )
-    elif msg_per_hour >= FREQ_ELEVATED:
-        return BehavioralSignal(
-            signal_type="frequency",
-            risk_level="MEDIUM",
-            description=f"Elevated messaging rate: {msg_per_hour:.0f} messages/hour",
-            evidence=[f"Last {len(recent)} messages in {time_span/60:.0f} minutes"],
-            score=msg_per_hour / FREQ_HIGH,
-        )
-    return None
-
-
-# ── Time-of-Day Analysis ─────────────────────────────────────────────────────
-
-def _analyze_time(messages: list[Message]) -> Optional[BehavioralSignal]:
-    """Detect late-night messaging (correlates with crisis risk)."""
-    if not messages:
-        return None
-
-    # Check most recent messages
-    recent = messages[-5:]
-    late_night_count = sum(1 for m in recent if m.timestamp.hour in HIGH_RISK_HOURS)
-    elevated_count = sum(1 for m in recent if m.timestamp.hour in ELEVATED_RISK_HOURS)
-
-    if late_night_count >= 3:
-        return BehavioralSignal(
-            signal_type="time",
-            risk_level="HIGH",
-            description=f"Late-night messaging pattern: {late_night_count}/5 messages between 1-4 AM",
-            evidence=[f"Message at {m.timestamp.strftime('%H:%M')}" for m in recent if m.timestamp.hour in HIGH_RISK_HOURS],
-            score=late_night_count / len(recent),
-        )
-    elif elevated_count >= 3:
-        return BehavioralSignal(
-            signal_type="time",
-            risk_level="MEDIUM",
-            description=f"Off-hours messaging: {elevated_count}/5 messages in elevated-risk window",
-            evidence=[f"Message at {m.timestamp.strftime('%H:%M')}" for m in recent if m.timestamp.hour in ELEVATED_RISK_HOURS],
-            score=elevated_count / len(recent) * 0.5,
-        )
-    return None
-
-
-# ── Withdrawal Detection ──────────────────────────────────────────────────────
-
-def _analyze_withdrawal(messages: list[Message]) -> Optional[BehavioralSignal]:
-    """Detect communication withdrawal (decreasing engagement)."""
-    user_msgs = [m for m in messages if m.role == "user"]
-    if len(user_msgs) < 10:
-        return None
-
-    # Split into first half and second half
-    mid = len(user_msgs) // 2
-    first_half = user_msgs[:mid]
-    second_half = user_msgs[mid:]
-
-    # Average message length as engagement proxy
-    first_avg_len = sum(len(m.content) for m in first_half) / len(first_half)
-    second_avg_len = sum(len(m.content) for m in second_half) / len(second_half)
-
-    # Time between messages
-    def avg_gap(msgs):
-        if len(msgs) < 2:
-            return 0
-        gaps = [(msgs[i+1].timestamp - msgs[i].timestamp).total_seconds() for i in range(len(msgs)-1)]
-        return sum(gaps) / len(gaps)
-
-    first_gap = avg_gap(first_half)
-    second_gap = avg_gap(second_half)
-
-    # Withdrawal = shorter messages AND longer gaps
-    length_ratio = second_avg_len / first_avg_len if first_avg_len > 0 else 1.0
-    gap_ratio = second_gap / first_gap if first_gap > 0 else 1.0
-
-    if length_ratio < 0.5 and gap_ratio > 2.0:
-        return BehavioralSignal(
-            signal_type="withdrawal",
-            risk_level="HIGH",
-            description="Significant withdrawal: messages shorter and less frequent",
-            evidence=[
-                f"Message length: {first_avg_len:.0f} -> {second_avg_len:.0f} chars ({length_ratio:.0%})",
-                f"Message gap: {first_gap/60:.0f}min -> {second_gap/60:.0f}min ({gap_ratio:.1f}x)",
-            ],
-            score=min(1.0, (1 - length_ratio) * 0.5 + (gap_ratio - 1) * 0.25),
-        )
-    elif length_ratio < 0.7 or gap_ratio > 1.5:
-        return BehavioralSignal(
-            signal_type="withdrawal",
-            risk_level="MEDIUM",
-            description="Moderate withdrawal: engagement decreasing",
-            evidence=[
-                f"Message length: {first_avg_len:.0f} -> {second_avg_len:.0f} chars",
-                f"Message gap: {first_gap/60:.0f}min -> {second_gap/60:.0f}min",
-            ],
-            score=(1 - length_ratio) * 0.3 + (gap_ratio - 1) * 0.15,
-        )
-    return None
-
-
-# ── Escalation Detection ─────────────────────────────────────────────────────
-
-def _analyze_escalation(messages: list[Message]) -> Optional[BehavioralSignal]:
-    """Detect rising crisis scores over recent messages."""
-    user_msgs = [m for m in messages if m.role == "user" and m.crisis_score > 0]
-    if len(user_msgs) < ESCALATION_WINDOW:
-        return None
-
-    recent = user_msgs[-ESCALATION_WINDOW:]
-    scores = [m.crisis_score for m in recent]
-
-    # Check for upward trend
-    if len(scores) < 3:
-        return None
-
-    # Simple linear trend: is score increasing?
-    first_half_avg = sum(scores[:len(scores)//2]) / (len(scores)//2)
-    second_half_avg = sum(scores[len(scores)//2:]) / (len(scores) - len(scores)//2)
-
-    if second_half_avg > first_half_avg * 1.5 and second_half_avg > 0.5:
-        return BehavioralSignal(
-            signal_type="escalation",
-            risk_level="HIGH",
-            description=f"Crisis escalation detected: scores rising from {first_half_avg:.2f} to {second_half_avg:.2f}",
-            evidence=[f"Score {i+1}: {s:.2f}" for i, s in enumerate(scores)],
-            score=min(1.0, second_half_avg),
-        )
-    elif second_half_avg > first_half_avg * 1.2 and second_half_avg > 0.3:
-        return BehavioralSignal(
-            signal_type="escalation",
-            risk_level="MEDIUM",
-            description=f"Mild escalation: scores trending up",
-            evidence=[f"Score {i+1}: {s:.2f}" for i, s in enumerate(scores)],
-            score=second_half_avg * 0.5,
-        )
-    return None
-
-
-# ── Combined Analysis ─────────────────────────────────────────────────────────
-
-def analyze_session(messages: list[Message]) -> list[BehavioralSignal]:
-    """Analyze a session for behavioral crisis signals.
-
-    Args:
-        messages: List of Message objects with timestamps, content, and crisis scores.
-
-    Returns:
-        List of BehavioralSignal objects, sorted by risk level (HIGH first).
-    """
-    signals = []
-
-    freq = _analyze_frequency(messages)
-    if freq:
-        signals.append(freq)
-
-    time_sig = _analyze_time(messages)
-    if time_sig:
-        signals.append(time_sig)
-
-    withdrawal = _analyze_withdrawal(messages)
-    if withdrawal:
-        signals.append(withdrawal)
-
-    escalation = _analyze_escalation(messages)
-    if escalation:
-        signals.append(escalation)
-
-    # Sort: HIGH first, then MEDIUM, then LOW
-    risk_order = {"HIGH": 0, "MEDIUM": 1, "LOW": 2}
-    signals.sort(key=lambda s: (risk_order.get(s.risk_level, 9), -s.score))
-
-    return signals
-
-
-def get_session_risk_level(signals: list[BehavioralSignal]) -> str:
-    """Get overall session risk from behavioral signals."""
-    if not signals:
-        return "NONE"
-    if any(s.risk_level == "HIGH" for s in signals):
-        return "HIGH"
-    if any(s.risk_level == "MEDIUM" for s in signals):
-        return "MEDIUM"
-    return "LOW"
-
-
-# ── Self-Test ─────────────────────────────────────────────────────────────────
-
-if __name__ == "__main__":
-    from datetime import timedelta
-
-    now = datetime.now(timezone.utc)
-
-    # Test: rapid-fire messaging
-    rapid_msgs = [
-        Message(timestamp=now - timedelta(minutes=i), content="help me", role="user")
-        for i in range(20, 0, -1)
-    ]
-    signals = analyze_session(rapid_msgs)
-    print(f"Rapid-fire: {[s.signal_type + ':' + s.risk_level for s in signals]}")
-    assert any(s.signal_type == "frequency" for s in signals), "Should detect frequency"
-
-    # Test: late-night
-    late_msgs = [
-        Message(timestamp=now.replace(hour=2, minute=i*5), content="cant sleep", role="user")
-        for i in range(5)
-    ]
-    signals = analyze_session(late_msgs)
-    print(f"Late-night: {[s.signal_type + ':' + s.risk_level for s in signals]}")
-    assert any(s.signal_type == "time" for s in signals), "Should detect time"
-
-    # Test: escalation
-    esc_msgs = [
-        Message(timestamp=now - timedelta(minutes=i*10), content="feeling bad",
-                role="user", crisis_score=0.1 + i*0.15)
-        for i in range(5, 0, -1)
-    ]
-    signals = analyze_session(esc_msgs)
-    print(f"Escalation: {[s.signal_type + ':' + s.risk_level for s in signals]}")
-    assert any(s.signal_type == "escalation" for s in signals), "Should detect escalation"
-
-    print("\nAll self-tests passed!")

index.html

@@ -993,6 +993,16 @@ Sovereignty and service always.`;
 
   function trapFocusInOverlay(e) {
     if (!crisisOverlay.classList.contains('active')) return;
+
+    // Escape: dismiss overlay (only when dismiss button is enabled after countdown)
+    if (e.key === 'Escape') {
+      e.preventDefault();
+      if (!overlayDismissBtn.disabled) {
+        overlayDismissBtn.click();
+      }
+      return;
+    }
+
     if (e.key !== 'Tab') return;
 
     var focusable = getOverlayFocusableElements();
@@ -1001,6 +1011,13 @@ Sovereignty and service always.`;
     var first = focusable[0];
     var last = focusable[focusable.length - 1];
 
+    // If focus escaped outside the overlay, bring it back
+    if (!crisisOverlay.contains(document.activeElement)) {
+      e.preventDefault();
+      first.focus();
+      return;
+    }
+
     if (e.shiftKey) {
       // Shift+Tab: if on first, wrap to last
       if (document.activeElement === first) {
@@ -1050,7 +1067,11 @@ Sovereignty and service always.`;
       }
     }, 1000);
 
-    overlayDismissBtn.focus();
+    // Focus the Call 988 link (always enabled) — not the disabled dismiss button
+    var callLink = crisisOverlay.querySelector('a.overlay-call');
+    if (callLink) {
+      callLink.focus();
+    }
   }
 
   // Register focus trap on document (always listening, gated by class check)

tests/test_crisis_overlay_focus_trap.py

@@ -52,6 +52,38 @@ class TestCrisisOverlayFocusTrap(unittest.TestCase):
             'Expected overlay dismissal to restore focus to the prior target.',
         )
 
+    def test_overlay_initial_focus_targets_enabled_element(self):
+        """Issue #69: overlay must not focus the disabled dismiss button on open."""
+        # The showOverlay function should NOT call overlayDismissBtn.focus()
+        # while the button is disabled. Instead it should focus an enabled element.
+        self.assertNotRegex(
+            self.html,
+            r"overlayDismissBtn\.disabled\s*=\s*true;.*overlayDismissBtn\.focus\(\)",
+            'showOverlay must not focus the dismiss button while it is disabled (issue #69).',
+        )
+        # Verify focus goes to the Call 988 link (always enabled)
+        self.assertIn(
+            "querySelector('a.overlay-call')",
+            self.html,
+            'Expected showOverlay to focus the Call 988 link on open.',
+        )
+
+    def test_overlay_escape_key_dismisses(self):
+        """Issue #69/95: Escape key should dismiss the overlay when countdown completes."""
+        self.assertRegex(
+            self.html,
+            r"e\.key\s*===\s*['\"]Escape['\"]",
+            'Expected Escape key handler in overlay focus trap.',
+        )
+
+    def test_overlay_focus_recovery_when_focus_escapes(self):
+        """Focus trap should recover focus if it escapes the overlay."""
+        self.assertRegex(
+            self.html,
+            r"crisisOverlay\.contains\(document\.activeElement\)",
+            'Focus trap should check if focus is still within the overlay.',
+        )
+
 
 if __name__ == '__main__':
     unittest.main()