feat: add concurrent agents with dependency system and delightful UI

Major feature implementation for parallel agent execution with dependency-aware
scheduling and an engaging multi-agent UI experience.

Backend Changes:
- Add parallel_orchestrator.py for concurrent feature processing
- Add api/dependency_resolver.py with cycle detection (Kahn's algorithm + DFS)
- Add atomic feature_claim_next() with retry limit and exponential backoff
- Fix circular dependency check arguments in 4 locations
- Add AgentTracker class for parsing agent output and emitting updates
- Add browser isolation with --isolated flag for Playwright MCP
- Extend WebSocket protocol with agent_update messages and log attribution
- Add WSAgentUpdateMessage schema with agent states and mascot names
- Fix WSProgressMessage to include in_progress field

New UI Components:
- AgentMissionControl: Dashboard showing active agents with collapsible activity
- AgentCard: Individual agent status with avatar and thought bubble
- AgentAvatar: SVG mascots (Spark, Fizz, Octo, Hoot, Buzz) with animations
- ActivityFeed: Recent activity stream with stable keys (no flickering)
- CelebrationOverlay: Confetti animation with click/Escape dismiss
- DependencyGraph: Interactive node graph visualization with dagre layout
- DependencyBadge: Visual indicator for feature dependencies
- ViewToggle: Switch between Kanban and Graph views
- KeyboardShortcutsHelp: Help overlay accessible via ? key

UI/UX Improvements:
- Celebration queue system to handle rapid success messages
- Accessibility attributes on AgentAvatar (role, aria-label, aria-live)
- Collapsible Recent Activity section with persisted preference
- Agent count display in header
- Keyboard shortcut G to toggle Kanban/Graph view
- Real-time thought bubbles and state animations

Bug Fixes:
- Fix circular dependency validation (swapped source/target arguments)
- Add MAX_CLAIM_RETRIES=10 to prevent stack overflow under contention
- Fix THOUGHT_PATTERNS to match actual [Tool: name] format
- Fix ActivityFeed key prop to prevent re-renders on new items
- Add featureId/agentIndex to log messages for proper attribution

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

autonomous_agent_demo.py

@@ -19,6 +19,12 @@ Example Usage:
 
     # YOLO mode: rapid prototyping without browser testing
     python autonomous_agent_demo.py --project-dir my-app --yolo
+
+    # Parallel execution with 3 concurrent agents (default)
+    python autonomous_agent_demo.py --project-dir my-app --parallel
+
+    # Parallel execution with 5 concurrent agents
+    python autonomous_agent_demo.py --project-dir my-app --parallel 5
 """
 
 import argparse
@@ -91,6 +97,24 @@ Authentication:
         help="Enable YOLO mode: rapid prototyping without browser testing",
     )
 
+    parser.add_argument(
+        "--parallel",
+        "-p",
+        type=int,
+        nargs="?",
+        const=3,
+        default=None,
+        metavar="N",
+        help="Enable parallel execution with N concurrent agents (default: 3, max: 5)",
+    )
+
+    parser.add_argument(
+        "--feature-id",
+        type=int,
+        default=None,
+        help="Work on a specific feature ID only (used by parallel orchestrator)",
+    )
+
     return parser.parse_args()
 
 
@@ -123,15 +147,30 @@ def main() -> None:
             return
 
     try:
-        # Run the agent (MCP server handles feature database)
-        asyncio.run(
-            run_autonomous_agent(
-                project_dir=project_dir,
-                model=args.model,
-                max_iterations=args.max_iterations,
-                yolo_mode=args.yolo,
+        if args.parallel is not None:
+            # Parallel execution mode
+            from parallel_orchestrator import run_parallel_orchestrator
+
+            print(f"Running in parallel mode with {args.parallel} concurrent agents")
+            asyncio.run(
+                run_parallel_orchestrator(
+                    project_dir=project_dir,
+                    max_concurrency=args.parallel,
+                    model=args.model,
+                    yolo_mode=args.yolo,
+                )
+            )
+        else:
+            # Standard single-agent mode (MCP server handles feature database)
+            asyncio.run(
+                run_autonomous_agent(
+                    project_dir=project_dir,
+                    model=args.model,
+                    max_iterations=args.max_iterations,
+                    yolo_mode=args.yolo,
+                    feature_id=args.feature_id,
+                )
             )
-        )
     except KeyboardInterrupt:
         print("\n\nInterrupted by user")
         print("To resume, run the same command again")