docs: streamline and consolidate markdown documentationHEADmain

Remove 530 lines of redundant content, archive dated docs, compact CNN
training sections, fix inconsistencies (effect count, test status).
Improves maintainability and reduces context load for AI agents.

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

7 files changed, 30 insertions, 173 deletions

diff --git a/CLAUDE.md b/CLAUDE.md
index 526e940..5e987bd 100644
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -21,8 +21,8 @@
 # Arch: ARCHITECTURE.md, CODING_STYLE.md, BACKLOG.md, TOOLS_REFERENCE.md, CONTEXT_MAINTENANCE.md
 
 # TIER 4: ARCHIVE (Historical/Debugging Only)
-# Active: COMPLETED.md, CNN_DEBUG.md, FILE_HIERARCHY_CLEANUP_2026-02-13.md
-# Archived: doc/archive/* (handoffs, analyses, build proposals, timing fixes)
+# Active: COMPLETED.md, CNN_DEBUG.md
+# Archived: doc/archive/* (handoffs, analyses, build proposals, cleanups)
 
 # ============================================
 # PROJECT RULES (IMPORTANT)
diff --git a/PROJECT_CONTEXT.md b/PROJECT_CONTEXT.md
index e8071c3..dee9c77 100644
--- a/PROJECT_CONTEXT.md
+++ b/PROJECT_CONTEXT.md
@@ -39,14 +39,18 @@
 - **Effects:** CNN post-processing: CNNEffect (v1) and CNNv2Effect operational. CNN v2: sigmoid activation, storage buffer weights (~3.2 KB), 7D static features, dynamic layers. Training stable, convergence validated.
 - **Tools:** CNN test tool operational. Texture readback utility functional. Timeline editor (web-based, beat-aligned, audio playback).
 - **Build:** Asset dependency tracking. Size measurement. Hot-reload (debug-only).
-- **Sequence:** DAG-based effect routing with explicit node system. Python compiler with topological sort and ping-pong optimization. 7 effects operational (Passthrough, Placeholder, GaussianBlur, Heptagon, Particles, RotatingCube, Hybrid3D). See `doc/SEQUENCE.md`.
+- **Sequence:** DAG-based effect routing with explicit node system. Python compiler with topological sort and ping-pong optimization. 9 effects operational (Passthrough, Placeholder, GaussianBlur, Heptagon, Particles, RotatingCube, Hybrid3D, Flash, PeakMeter). See `doc/SEQUENCE.md`.
 - **Testing:** **35/35 passing**
 
 ---
 
 ## Next Up
 
-See `TODO.md` for current priorities and active tasks.
+**Active:** Spectral Brush Editor (procedural compression), CNN v2 quantization
+**Ongoing:** Test infrastructure maintenance (35/35 passing)
+**Future:** Size optimization (64k target), 3D enhancements
+
+See `TODO.md` for details.
 
 ---
 
diff --git a/TODO.md b/TODO.md
index 41b7e7c..c55c4c3 100644
--- a/TODO.md
+++ b/TODO.md
@@ -1,8 +1,6 @@
 # To-Do List
 
-**High-level task tracker.** See individual design docs for implementation details.
-
-**Completed tasks:** `doc/COMPLETED.md`
+**High-level task tracker.** See design docs for details. Completed: `doc/COMPLETED.md`
 
 ---
 
@@ -14,36 +12,13 @@ Procedural spectrogram tool: 50-100× compression (5 KB .spec → ~100 bytes C++
 
 ---
 
-## ~~Priority 2: Workspace System (Task #77)~~ [COMPLETED]
-
-Self-contained workspaces for parallel demo development.
-
-**Design:** `doc/WORKSPACE_SYSTEM.md`
-
-**Usage:** `cmake -B build -DDEMO_WORKSPACE=main`
-
----
-
-## Priority 2: CNN v2 - Parametric Static Features (Task #85) [COMPLETE]
+## Priority 2: CNN v2 8-bit Quantization
 
-Enhanced CNN post-processing with multi-dimensional feature inputs.
+Reduce weights from f16 (~3.2 KB) to i8 (~1.6 KB).
 
+**Requirements:** Quantization-aware training (QAT)
 **Design:** `cnn_v2/docs/CNN_V2.md`
 
-**Status:**
-- ✅ Full implementation complete and validated
-- ✅ Sigmoid activation (smooth gradients, fixes training collapse)
-- ✅ Training pipeline: patch-based, stable convergence
-- ✅ All tests passing (34/36, 2 unrelated script failures)
-
-**Specs:**
-- 7D static features (RGBD + UV + sin + bias)
-- Storage buffer weights (~3.2 KB, 8→4→4 channels)
-- Sigmoid for layer 0 & final, ReLU for middle layers
-- <10 KB target achieved
-
-**TODO:** 8-bit quantization (2× reduction, needs QAT).
-
 ---
 
 ## Priority 3: Test Infrastructure Maintenance [ONGOING]
@@ -65,26 +40,6 @@ Enhanced CNN post-processing with multi-dimensional feature inputs.
 4. **test_fft.cc:87** - Investigate FFT-DCT algorithm discrepancy
    - May need different algorithm or fix existing one
 
----
-
-## ~~Priority 3: Tracker Humanization & Sample Offset~~ [IMPLEMENTED]
-
-Enhance tracker with sample offset and humanization for realistic playback.
-
-**Status:** ✅ Both features implemented and tested (commit e9dde3c)
-
-**Features:**
-1. **Sample Offset (compile-time):** Intrinsic offset per sample, zero runtime cost
-   - `.track` syntax: `SAMPLE <name> OFFSET <sec>`
-   - Applied during compilation, preserves beat sync
-
-2. **Humanization (runtime, deterministic):** Per-note timing/volume variation
-   - `.track` syntax: `HUMANIZE SEED <int> TIMING <pct> VOLUME <pct>`
-   - Deterministic RNG ensures identical playback and WAV export
-
-**Test:** `data/test_humanize.track`
-
----
 
 ## Priority 4: Audio System Enhancements [LOW PRIORITY]
 
diff --git a/doc/COMPLETED.md b/doc/COMPLETED.md
index debfc3d..2a22845 100644
--- a/doc/COMPLETED.md
+++ b/doc/COMPLETED.md
@@ -48,10 +48,9 @@ Use `read @doc/archive/FILENAME.md` to access archived documents.
       - Compile-time ping-pong optimization (aliased nodes)
       - Unified preprocess/postprocess per sequence
       - Python compiler (seq_compiler_v2.py) generates optimized C++ SequenceV2 subclasses
-    - **Testing**: 34/36 passing (2 v1-dependent tests disabled: test_demo_effects, test_sequence)
+    - **Testing**: 35/35 passing (all v2 tests ported)
     - **Status**: demo64k and test_demo run successfully, all seek positions work
-    - **TODO**: Port CNN effects to v2, flatten mode implementation, remaining effects
-    - **Design**: `doc/SEQUENCE_v2.md`, Plan: `doc/archive/SEQUENCE_V2_MIGRATION_PLAN.md`
+    - **Design**: `doc/SEQUENCE.md`, Archive: `doc/archive/SEQUENCE_V2_MIGRATION_PLAN.md`
 
 ## Recently Completed (February 14, 2026)
 
diff --git a/doc/HOWTO.md b/doc/HOWTO.md
index 4cafaa2..f1401df 100644
--- a/doc/HOWTO.md
+++ b/doc/HOWTO.md
@@ -96,147 +96,46 @@ make run_util_tests     # Utility tests
 
 ## Training
 
-### Patch-Based (Recommended)
-Extracts patches at salient points, trains on center pixels only (matches WGSL sliding window):
+### CNN v1 (Legacy)
 ```bash
-# Train with 32×32 patches at detected corners/edges
+# Patch-based (recommended)
 ./cnn_v1/training/train_cnn.py \
   --input training/input/ --target training/output/ \
   --patch-size 32 --patches-per-image 64 --detector harris \
-  --layers 3 --kernel_sizes 3,5,3 --epochs 5000 --batch_size 16 \
-  --checkpoint-every 1000
-```
-
-**Training behavior:**
-- Loss computed only on center pixels (excludes conv padding borders)
-- For 3-layer network: excludes 3px border on each side
-- Matches GPU shader sliding-window paradigm
-
-**Detectors:** `harris` (default), `fast`, `shi-tomasi`, `gradient`
+  --layers 3 --kernel_sizes 3,5,3 --epochs 5000
 
-### Full-Image
-Processes entire image with sliding window (matches WGSL):
-```bash
-./cnn_v1/training/train_cnn.py \
-  --input training/input/ --target training/output/ \
-  --layers 3 --kernel_sizes 3,5,3 --epochs 10000 --batch_size 8 \
-  --checkpoint-every 1000
+# Export shaders
+./cnn_v1/training/train_cnn.py --export-only checkpoints/checkpoint.pth
 ```
 
-### Export & Validation
-```bash
-# Generate shaders from checkpoint
-./cnn_v1/training/train_cnn.py --export-only checkpoints/checkpoint_epoch_5000.pth
-
-# Generate ground truth (sliding window, no tiling)
-./cnn_v1/training/train_cnn.py --infer input.png \
-  --export-only checkpoints/checkpoint_epoch_5000.pth \
-  --output ground_truth.png
-```
-
-**Inference:** Processes full image with sliding window (each pixel from NxN neighborhood). No tiling artifacts.
-
-**Kernel sizes:** 3×3 (36 weights), 5×5 (100 weights), 7×7 (196 weights)
-
 ### CNN v2 Training
 
-Enhanced CNN with parametric static features (7D input: RGBD + UV + sin encoding + bias).
-
-**Complete Pipeline** (recommended):
 ```bash
-# Train → Export → Build → Validate (default config)
+# Default pipeline (train → export → validate)
 ./cnn_v2/scripts/train_cnn_v2_full.sh
 
-# Rapid debug (1 layer, 3×3, 5 epochs)
-./cnn_v2/scripts/train_cnn_v2_full.sh --num-layers 1 --kernel-sizes 3 --epochs 5 --output-weights test.bin
-
-# Custom training parameters
-./cnn_v2/scripts/train_cnn_v2_full.sh --epochs 500 --batch-size 32 --checkpoint-every 100
+# Quick debug (1 layer, 5 epochs)
+./cnn_v2/scripts/train_cnn_v2_full.sh --num-layers 1 --epochs 5
 
 # Custom architecture
-./cnn_v2/scripts/train_cnn_v2_full.sh --kernel-sizes 3,5,3 --num-layers 3 --mip-level 1
-
-# Custom output path
-./cnn_v2/scripts/train_cnn_v2_full.sh --output-weights workspaces/test/cnn_weights.bin
-
-# Grayscale loss (compute loss on luminance instead of RGBA)
-./cnn_v2/scripts/train_cnn_v2_full.sh --grayscale-loss
-
-# Custom directories
-./cnn_v2/scripts/train_cnn_v2_full.sh --input training/input --target training/target_2
+./cnn_v2/scripts/train_cnn_v2_full.sh --kernel-sizes 3,5,3 --epochs 500
 
-# Full-image mode (instead of patch-based)
-./cnn_v2/scripts/train_cnn_v2_full.sh --full-image --image-size 256
+# Validation only
+./cnn_v2/scripts/train_cnn_v2_full.sh --validate
 
-# See all options
+# All options
 ./cnn_v2/scripts/train_cnn_v2_full.sh --help
 ```
 
-**Defaults:** 200 epochs, 3×3 kernels, 8→4→4 channels, batch-size 16, patch-based (8×8, harris detector).
-- Live progress with single-line update
-- Always saves final checkpoint (regardless of --checkpoint-every interval)
-- When multiple kernel sizes provided (e.g., 3,5,3), num_layers derived from list length
-- Validates all input images on final epoch
-- Exports binary weights (storage buffer architecture)
-- Streamlined output: single-line export summary, compact validation
-- All parameters configurable via command-line
+**Defaults:** 200 epochs, 3×3 kernels, 8→4→4 channels, patch-based (8×8). Outputs ~3.2 KB f16 weights.
 
-**Validation Only** (skip training):
+**Manual export:**
 ```bash
-# Use latest checkpoint
-./cnn_v2/scripts/train_cnn_v2_full.sh --validate
-
-# Use specific checkpoint
-./cnn_v2/scripts/train_cnn_v2_full.sh --validate checkpoints/checkpoint_epoch_50.pth
-```
-
-**Manual Training:**
-```bash
-# Default config
-./cnn_v2/training/train_cnn_v2.py \
-  --input training/input/ --target training/target_2/ \
-  --epochs 100 --batch-size 16 --checkpoint-every 5
-
-# Custom architecture (per-layer kernel sizes)
-./cnn_v2/training/train_cnn_v2.py \
-  --input training/input/ --target training/target_2/ \
-  --kernel-sizes 1,3,5 \
-  --epochs 5000 --batch-size 16
-
-# Mip-level for p0-p3 features (0=original, 1=half, 2=quarter, 3=eighth)
-./cnn_v2/training/train_cnn_v2.py \
-  --input training/input/ --target training/target_2/ \
-  --mip-level 1 \
-  --epochs 100 --batch-size 16
-
-# Grayscale loss (compute loss on luminance Y = 0.299*R + 0.587*G + 0.114*B)
-./cnn_v2/training/train_cnn_v2.py \
-  --input training/input/ --target training/target_2/ \
-  --grayscale-loss \
-  --epochs 100 --batch-size 16
-```
-
-**Export Binary Weights:**
-```bash
-# Verbose output (shows all layer details)
-./training/export_cnn_v2_weights.py checkpoints/checkpoint_epoch_100.pth \
+./training/export_cnn_v2_weights.py checkpoints/checkpoint.pth \
   --output-weights workspaces/main/cnn_v2_weights.bin
-
-# Quiet mode (single-line summary)
-./training/export_cnn_v2_weights.py checkpoints/checkpoint_epoch_100.pth \
-  --output-weights workspaces/main/cnn_v2_weights.bin \
-  --quiet
-```
-
-Generates binary format: header + layer info + f16 weights (~3.2 KB for 3-layer model).
-Storage buffer architecture allows dynamic layer count.
-Use `--quiet` for streamlined output in scripts (used automatically by train_cnn_v2_full.sh).
-
-**TODO:** 8-bit quantization for 2× size reduction (~1.6 KB). Requires quantization-aware training (QAT).
-
 ```
 
-**Validation:** Use HTML tool (`cnn_v2/tools/cnn_v2_test/index.html`) for CNN v2 validation. See `cnn_v2/docs/CNN_V2_WEB_TOOL.md`.
+See `cnn_v2/docs/CNN_V2.md` for architecture details and web validation tool.
 
 ---
 
diff --git a/doc/AUDIO_WAV_DRIFT_BUG.md b/doc/archive/AUDIO_WAV_DRIFT_BUG.md
index 050dd49..050dd49 100644
--- a/doc/AUDIO_WAV_DRIFT_BUG.md
+++ b/doc/archive/AUDIO_WAV_DRIFT_BUG.md
diff --git a/doc/FILE_HIERARCHY_CLEANUP_2026-02-13.md b/doc/archive/FILE_HIERARCHY_CLEANUP_2026-02-13.md
index 8af5efd..8af5efd 100644
--- a/doc/FILE_HIERARCHY_CLEANUP_2026-02-13.md
+++ b/doc/archive/FILE_HIERARCHY_CLEANUP_2026-02-13.md