feat: add pipeline introspection demo mode

- Add PipelineIntrospectionSource that renders live ASCII DAG with metrics
- Add PipelineMetricsSensor exposing pipeline performance as sensor values
- Add PipelineIntrospectionDemo controller with 3-phase animation:
  - Phase 1: Toggle effects one at a time (3s each)
  - Phase 2: LFO drives intensity default→max→min→default
  - Phase 3: All effects with shared LFO (infinite loop)
- Add pipeline-inspect preset
- Add get_frame_times() to Pipeline for sparkline data
- Add tests for new components
- Update mise.toml with pipeline-inspect preset task

engine/sensors/pipeline_metrics.py

@@ -0,0 +1,114 @@
+"""
+Pipeline metrics sensor - Exposes pipeline performance data as sensor values.
+
+This sensor reads metrics from a Pipeline instance and provides them
+as sensor values that can drive effect parameters.
+
+Example:
+    sensor = PipelineMetricsSensor(pipeline)
+    sensor.read()  # Returns SensorValue with total_ms, fps, etc.
+"""
+
+from typing import TYPE_CHECKING
+
+from engine.sensors import Sensor, SensorValue
+
+if TYPE_CHECKING:
+    from engine.pipeline.controller import Pipeline
+
+
+class PipelineMetricsSensor(Sensor):
+    """Sensor that reads metrics from a Pipeline instance.
+
+    Provides real-time performance data:
+    - total_ms: Total frame time in milliseconds
+    - fps: Calculated frames per second
+    - stage_timings: Dict of stage name -> duration_ms
+
+    Can be bound to effect parameters for reactive visuals.
+    """
+
+    def __init__(self, pipeline: "Pipeline | None" = None, name: str = "pipeline"):
+        self._pipeline = pipeline
+        self.name = name
+        self.unit = "ms"
+        self._last_values: dict[str, float] = {
+            "total_ms": 0.0,
+            "fps": 0.0,
+            "avg_ms": 0.0,
+            "min_ms": 0.0,
+            "max_ms": 0.0,
+        }
+
+    @property
+    def available(self) -> bool:
+        return self._pipeline is not None
+
+    def set_pipeline(self, pipeline: "Pipeline") -> None:
+        """Set or update the pipeline to read metrics from."""
+        self._pipeline = pipeline
+
+    def read(self) -> SensorValue | None:
+        """Read current metrics from the pipeline."""
+        if not self._pipeline:
+            return None
+
+        try:
+            metrics = self._pipeline.get_metrics_summary()
+        except Exception:
+            return None
+
+        if not metrics or "error" in metrics:
+            return None
+
+        self._last_values["total_ms"] = metrics.get("total_ms", 0.0)
+        self._last_values["fps"] = metrics.get("fps", 0.0)
+        self._last_values["avg_ms"] = metrics.get("avg_ms", 0.0)
+        self._last_values["min_ms"] = metrics.get("min_ms", 0.0)
+        self._last_values["max_ms"] = metrics.get("max_ms", 0.0)
+
+        # Provide total_ms as primary value (for LFO-style effects)
+        return SensorValue(
+            sensor_name=self.name,
+            value=self._last_values["total_ms"],
+            timestamp=0.0,
+            unit=self.unit,
+        )
+
+    def get_stage_timing(self, stage_name: str) -> float:
+        """Get timing for a specific stage."""
+        if not self._pipeline:
+            return 0.0
+        try:
+            metrics = self._pipeline.get_metrics_summary()
+            stages = metrics.get("stages", {})
+            return stages.get(stage_name, {}).get("avg_ms", 0.0)
+        except Exception:
+            return 0.0
+
+    def get_all_timings(self) -> dict[str, float]:
+        """Get all stage timings as a dict."""
+        if not self._pipeline:
+            return {}
+        try:
+            metrics = self._pipeline.get_metrics_summary()
+            return metrics.get("stages", {})
+        except Exception:
+            return {}
+
+    def get_frame_history(self) -> list[float]:
+        """Get historical frame times for sparklines."""
+        if not self._pipeline:
+            return []
+        try:
+            return self._pipeline.get_frame_times()
+        except Exception:
+            return []
+
+    def start(self) -> bool:
+        """Start the sensor (no-op for read-only metrics)."""
+        return True
+
+    def stop(self) -> None:
+        """Stop the sensor (no-op for read-only metrics)."""
+        pass