fix: change default colormap from inferno to viridis

SKILL.md

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+---
+name: depth-estimation
+description: "Real-time depth map privacy transforms using Depth Anything v2 (CoreML + PyTorch)"
+version: 1.2.0
+category: privacy
+
+parameters:
+  - name: model
+    label: "Depth Model"
+    type: select
+    options: ["depth-anything-v2-small", "depth-anything-v2-base", "depth-anything-v2-large"]
+    default: "depth-anything-v2-small"
+    group: Model
+
+  - name: variant
+    label: "CoreML Variant (macOS)"
+    type: select
+    options: ["DepthAnythingV2SmallF16", "DepthAnythingV2SmallF16INT8", "DepthAnythingV2SmallF32"]
+    default: "DepthAnythingV2SmallF16"
+    group: Model
+
+  - name: blend_mode
+    label: "Display Mode"
+    type: select
+    options: ["depth_only", "overlay", "side_by_side"]
+    default: "depth_only"
+    group: Display
+
+  - name: opacity
+    label: "Overlay Opacity"
+    type: number
+    min: 0.0
+    max: 1.0
+    default: 0.5
+    group: Display
+
+  - name: colormap
+    label: "Depth Colormap"
+    type: select
+    options: ["inferno", "viridis", "plasma", "magma", "jet", "turbo", "hot", "cool"]
+    default: "viridis"
+    group: Display
+
+  - name: device
+    label: "Device"
+    type: select
+    options: ["auto", "cpu", "cuda", "mps"]
+    default: "auto"
+    group: Performance
+
+capabilities:
+  live_transform:
+    script: scripts/transform.py
+    description: "Real-time depth estimation overlay on live feed"
+---
+
+# Depth Estimation (Privacy)
+
+Real-time monocular depth estimation using Depth Anything v2. Transforms camera feeds with colorized depth maps — near objects appear warm, far objects appear cool.
+
+When used for **privacy mode**, the `depth_only` blend mode fully anonymizes the scene while preserving spatial layout and activity, enabling security monitoring without revealing identities.
+
+## Hardware Backends
+
+| Platform | Backend | Runtime | Model |
+|----------|---------|---------|-------|
+| **macOS** | CoreML | Apple Neural Engine | `apple/coreml-depth-anything-v2-small` (.mlpackage) |
+| Linux/Windows | PyTorch | CUDA / CPU | `depth-anything/Depth-Anything-V2-Small` (.pth) |
+
+On macOS, CoreML runs on the Neural Engine, leaving the GPU free for other tasks. The model is auto-downloaded from HuggingFace and stored at `~/.aegis-ai/models/feature-extraction/`.
+
+## What You Get
+
+- **Privacy anonymization** — depth-only mode hides all visual identity
+- **Depth overlays** on live camera feeds
+- **3D scene understanding** — spatial layout of the scene
+- **CoreML acceleration** — Neural Engine on Apple Silicon (3-5x faster than MPS)
+
+## Interface: TransformSkillBase
+
+This skill implements the `TransformSkillBase` interface. Any new privacy skill can be created by subclassing `TransformSkillBase` and implementing two methods:
+
+```python
+from transform_base import TransformSkillBase
+
+class MyPrivacySkill(TransformSkillBase):
+    def load_model(self, config):
+        # Load your model, return {"model": "...", "device": "..."}
+        ...
+
+    def transform_frame(self, image, metadata):
+        # Transform BGR image, return BGR image
+        ...
+```
+
+## Protocol
+
+### Aegis → Skill (stdin)
+```jsonl
+{"event": "frame", "frame_id": "cam1_1710001", "camera_id": "front_door", "frame_path": "/tmp/frame.jpg", "timestamp": "..."}
+{"command": "config-update", "config": {"opacity": 0.8, "blend_mode": "overlay"}}
+{"command": "stop"}
+```
+
+### Skill → Aegis (stdout)
+```jsonl
+{"event": "ready", "model": "coreml-DepthAnythingV2SmallF16", "device": "neural_engine", "backend": "coreml"}
+{"event": "transform", "frame_id": "cam1_1710001", "camera_id": "front_door", "transform_data": "<base64 JPEG>"}
+{"event": "perf_stats", "total_frames": 50, "timings_ms": {"transform": {"avg": 12.5, ...}}}
+```
+
+## Setup
+
+```bash
+python3 -m venv .venv && source .venv/bin/activate
+pip install -r requirements.txt
+```