feat: domestic flights, road traffic, CCTV webcams, AI situation brief

Four new intelligence domains for the dashboard:

1. Domestic flights (OpenSky) — global airborne aircraft count by
   region with commercial/general breakdown. No API key needed.

2. Road traffic (TomTom) — real-time congestion % for 20 major world
   cities + traffic incidents in 5 strategic regions. Needs
   TOMTOM_API_KEY (free 2500 req/day at developer.tomtom.com).

3. CCTV webcams (Windy) — public traffic camera locations worldwide.
   Needs WINDY_API_KEY (free 100 req/day at api.windy.com).

4. AI situation brief (Ollama) — LLM-generated 3-paragraph
   intelligence brief synthesizing all dashboard data. Uses local
   Ollama (llama3.2). Falls back to structured metrics summary.

New files: sources/traffic.py, sources/webcams.py, analysis/situation.py
Modified: sources/aviation.py (+fetch_domestic_flights), dashboard/app.py,
dashboard/index.html (drawer sections + HUD pills for all 4 domains).

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

src/world_intel_mcp/dashboard/app.py

@@ -41,10 +41,13 @@ from world_intel_mcp.sources import (
     social,
     nuclear,
     service_status,
+    traffic,
+    webcams,
 )
 from world_intel_mcp.analysis.alerts import fetch_alert_digest, fetch_weekly_trends
 from world_intel_mcp.analysis.posture import fetch_strategic_posture
 from world_intel_mcp.analysis.exposure import fetch_population_exposure
+from world_intel_mcp.analysis.situation import fetch_situation_brief
 from world_intel_mcp.sources.fleet import fetch_fleet_report
 from world_intel_mcp.config.countries import INTEL_HOTSPOTS, STRATEGIC_WATERWAYS
 from world_intel_mcp.config.geospatial import MILITARY_BASES, STRATEGIC_PORTS, PIPELINES, NUCLEAR_FACILITIES
@@ -115,6 +118,10 @@ async def _fetch_overview() -> dict:
         "strategic_posture": fetch_strategic_posture(fetcher),
         "fleet_report": fetch_fleet_report(fetcher),
         "population_exposure": fetch_population_exposure(fetcher),
+        "domestic_flights": aviation.fetch_domestic_flights(fetcher),
+        "traffic_flow": traffic.fetch_traffic_flow(fetcher),
+        "traffic_incidents": traffic.fetch_traffic_incidents(fetcher),
+        "webcams": webcams.fetch_webcams(fetcher),
     }
 
     # Per-coro timeout so no single slow source blocks the entire dashboard.
@@ -183,6 +190,15 @@ async def _fetch_overview() -> dict:
         "count": len(CABLE_CORRIDORS),
     }
 
+    # AI situational brief (runs after main gather so it has all data)
+    try:
+        result["situation_brief"] = await asyncio.wait_for(
+            fetch_situation_brief(result), timeout=35.0,
+        )
+    except Exception as exc:
+        logger.warning("Situation brief failed: %s", exc)
+        result["situation_brief"] = {"error": str(exc)}
+
     # Attach source health + timestamp
     result["source_health"] = _breaker.status() if _breaker else {}
     result["cache_stats"] = _cache.stats() if _cache else {}