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lib/channels/abber/abber.md

@@ -1,5 +1,22 @@
 # ABBER: Aberration Bands
 
+| Property         | Value                            |
+| ---------------- | -------------------------------- |
+| **Category**     | Channel                        |
+| **Inputs**       | Source (close)                          |
+| **Parameters**   | `period`, `multiplier` (default 2.0)                      |
+| **Outputs**      | Multiple series (Upper, Lower)                       |
+| **Output range** | Tracks input                     |
+| **Warmup**       | `period` bars                          |
+
+### TL;DR
+
+- ABBER measures price deviation from a central moving average using mean absolute deviation rather than standard deviation, producing dynamic bands ...
+- Parameterized by `period`, `multiplier` (default 2.0).
+- Output range: Tracks input.
+- Requires `period` bars of warmup before first valid output (IsHot = true).
+- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
+
 ABBER measures price deviation from a central moving average using mean absolute deviation rather than standard deviation, producing dynamic bands that adapt to volatility while remaining robust against extreme outliers. Where Bollinger Bands amplify outliers through squaring (the $L^2$ norm), ABBER uses raw absolute differences (the $L^1$ norm), so bands respond to typical price behavior rather than the occasional spike that yanks everything sideways. For a 20-period window with a 2.0 multiplier, ABBER contains approximately 89% of normally-distributed price action, but its real advantage emerges with fat-tailed distributions where standard deviation overreacts to single-bar anomalies.
 
 ## Historical Context