feat(pipeline): add metrics collection and v2 run mode

- Add RenderStage adapter that handles rendering pipeline
- Add EffectPluginStage with proper EffectContext
- Add DisplayStage with init handling
- Add ItemsStage for pre-fetched items
- Add metrics collection to Pipeline (StageMetrics, FrameMetrics)
- Add get_metrics_summary() and reset_metrics() methods
- Add --pipeline and --pipeline-preset flags for v2 mode
- Add PipelineNode.metrics for self-documenting introspection
- Add introspect_new_pipeline() method with performance data
- Add mise tasks: run-v2, run-v2-demo, run-v2-poetry, run-v2-websocket, run-v2-firehose

engine/pipeline.py

@@ -36,6 +36,7 @@ class PipelineNode:
     description: str = ""
     inputs: list[str] | None = None
     outputs: list[str] | None = None
+    metrics: dict | None = None  # Performance metrics (avg_ms, min_ms, max_ms)
 
 
 class PipelineIntrospector:
@@ -76,6 +77,14 @@ class PipelineIntrospector:
             if node.description:
                 label += f"\\n{node.description}"
 
+            if node.metrics:
+                avg = node.metrics.get("avg_ms", 0)
+                if avg > 0:
+                    label += f"\\n⏱ {avg:.1f}ms"
+                    impact = node.metrics.get("impact_pct", 0)
+                    if impact > 0:
+                        label += f" ({impact:.0f}%)"
+
             node_entry = f'    {node_id}["{label}"]'
 
             if "DataSource" in node.name or "SourceRegistry" in node.name:
@@ -501,6 +510,78 @@ class PipelineIntrospector:
                 )
             )
 
+    def introspect_new_pipeline(self, pipeline=None) -> None:
+        """Introspect new unified pipeline stages with metrics.
+
+        Args:
+            pipeline: Optional Pipeline instance to collect metrics from
+        """
+
+        stages_info = [
+            (
+                "ItemsSource",
+                "engine.pipeline.adapters",
+                "ItemsStage",
+                "Provides pre-fetched items",
+            ),
+            (
+                "Render",
+                "engine.pipeline.adapters",
+                "RenderStage",
+                "Renders items to buffer",
+            ),
+            (
+                "Effect",
+                "engine.pipeline.adapters",
+                "EffectPluginStage",
+                "Applies effect",
+            ),
+            (
+                "Display",
+                "engine.pipeline.adapters",
+                "DisplayStage",
+                "Outputs to display",
+            ),
+        ]
+
+        metrics = None
+        if pipeline and hasattr(pipeline, "get_metrics_summary"):
+            metrics = pipeline.get_metrics_summary()
+            if "error" in metrics:
+                metrics = None
+
+        total_avg = metrics.get("pipeline", {}).get("avg_ms", 0) if metrics else 0
+
+        for stage_name, module, class_name, desc in stages_info:
+            node_metrics = None
+            if metrics and "stages" in metrics:
+                for name, stats in metrics["stages"].items():
+                    if stage_name.lower() in name.lower():
+                        impact_pct = (
+                            (stats.get("avg_ms", 0) / total_avg * 100)
+                            if total_avg > 0
+                            else 0
+                        )
+                        node_metrics = {
+                            "avg_ms": stats.get("avg_ms", 0),
+                            "min_ms": stats.get("min_ms", 0),
+                            "max_ms": stats.get("max_ms", 0),
+                            "impact_pct": impact_pct,
+                        }
+                        break
+
+            self.add_node(
+                PipelineNode(
+                    name=f"Pipeline: {stage_name}",
+                    module=module,
+                    class_name=class_name,
+                    description=desc,
+                    inputs=["data"],
+                    outputs=["data"],
+                    metrics=node_metrics,
+                )
+            )
+
     def run(self) -> str:
         """Run full introspection."""
         self.introspect_sources()