feat: Add fast startup fetch and background caching

- Add  for quick startup using first N feeds
- Add background thread for full fetch and caching
- Update  to use fast fetch
- Update docs and skills

engine/pipeline/presets.py

@@ -11,11 +11,14 @@ Loading order:
 """
 
 from dataclasses import dataclass, field
-from typing import Any
+from typing import TYPE_CHECKING, Any
 
 from engine.display import BorderMode
 from engine.pipeline.params import PipelineParams
 
+if TYPE_CHECKING:
+    from engine.pipeline.controller import PipelineConfig
+
 
 def _load_toml_presets() -> dict[str, Any]:
     """Load presets from TOML file."""
@@ -55,9 +58,10 @@ class PipelinePreset:
     viewport_width: int = 80  # Viewport width in columns
     viewport_height: int = 24  # Viewport height in rows
     source_items: list[dict[str, Any]] | None = None  # For ListDataSource
+    enable_metrics: bool = True  # Enable performance metrics collection
 
     def to_params(self) -> PipelineParams:
-        """Convert to PipelineParams."""
+        """Convert to PipelineParams (runtime configuration)."""
         from engine.display import BorderMode
 
         params = PipelineParams()
@@ -72,10 +76,27 @@ class PipelinePreset:
         )
         params.camera_mode = self.camera
         params.effect_order = self.effects.copy()
-        # Note: camera_speed, viewport_width/height are not stored in PipelineParams
-        # They are used directly from the preset object in pipeline_runner.py
+        params.camera_speed = self.camera_speed
+        # Note: viewport_width/height are read from PipelinePreset directly
+        # in pipeline_runner.py, not from PipelineParams
         return params
 
+    def to_config(self) -> "PipelineConfig":
+        """Convert to PipelineConfig (static pipeline construction config).
+
+        PipelineConfig is used once at pipeline initialization and contains
+        the core settings that don't change during execution.
+        """
+        from engine.pipeline.controller import PipelineConfig
+
+        return PipelineConfig(
+            source=self.source,
+            display=self.display,
+            camera=self.camera,
+            effects=self.effects.copy(),
+            enable_metrics=self.enable_metrics,
+        )
+
     @classmethod
     def from_yaml(cls, name: str, data: dict[str, Any]) -> "PipelinePreset":
         """Create a PipelinePreset from YAML data."""
@@ -91,6 +112,7 @@ class PipelinePreset:
             viewport_width=data.get("viewport_width", 80),
             viewport_height=data.get("viewport_height", 24),
             source_items=data.get("source_items"),
+            enable_metrics=data.get("enable_metrics", True),
         )