refactor: reorganize skills into sub-categories

The skills directory was getting disorganized — mlops alone had 40
skills in a flat list, and 12 categories were singletons with just
one skill each.

Code change:
- prompt_builder.py: Support sub-categories in skill scanner.
  skills/mlops/training/axolotl/SKILL.md now shows as category
  'mlops/training' instead of just 'mlops'. Backwards-compatible
  with existing flat structure.

Split mlops (40 skills) into 7 sub-categories:
- mlops/training (12): accelerate, axolotl, flash-attention,
  grpo-rl-training, peft, pytorch-fsdp, pytorch-lightning,
  simpo, slime, torchtitan, trl-fine-tuning, unsloth
- mlops/inference (8): gguf, guidance, instructor, llama-cpp,
  obliteratus, outlines, tensorrt-llm, vllm
- mlops/models (6): audiocraft, clip, llava, segment-anything,
  stable-diffusion, whisper
- mlops/vector-databases (4): chroma, faiss, pinecone, qdrant
- mlops/evaluation (5): huggingface-tokenizers,
  lm-evaluation-harness, nemo-curator, saelens, weights-and-biases
- mlops/cloud (2): lambda-labs, modal
- mlops/research (1): dspy

Merged singleton categories:
- gifs → media (gif-search joins youtube-content)
- music-creation → media (heartmula, songsee)
- diagramming → creative (excalidraw joins ascii-art)
- ocr-and-documents → productivity
- domain → research (domain-intel)
- feeds → research (blogwatcher)
- market-data → research (polymarket)

Fixed misplaced skills:
- mlops/code-review → software-development (not ML-specific)
- mlops/ml-paper-writing → research (academic writing)

Added DESCRIPTION.md files for all new/updated categories.

skills/music-creation/songsee/SKILL.md

@@ -1,80 +0,0 @@
----
-name: songsee
-description: Generate spectrograms and audio feature visualizations (mel, chroma, MFCC, tempogram, etc.) from audio files via CLI. Useful for audio analysis, music production debugging, and visual documentation.
-version: 1.0.0
-author: community
-license: MIT
-metadata:
-  hermes:
-    tags: [Audio, Visualization, Spectrogram, Music, Analysis]
-    homepage: https://github.com/steipete/songsee
----
-
-# songsee
-
-Generate spectrograms and multi-panel audio feature visualizations from audio files.
-
-## Prerequisites
-
-Requires [Go](https://go.dev/doc/install):
-```bash
-go install github.com/steipete/songsee/cmd/songsee@latest
-```
-
-Optional: `ffmpeg` for formats beyond WAV/MP3.
-
-## Quick Start
-
-```bash
-# Basic spectrogram
-songsee track.mp3
-
-# Save to specific file
-songsee track.mp3 -o spectrogram.png
-
-# Multi-panel visualization grid
-songsee track.mp3 --viz spectrogram,mel,chroma,hpss,selfsim,loudness,tempogram,mfcc,flux
-
-# Time slice (start at 12.5s, 8s duration)
-songsee track.mp3 --start 12.5 --duration 8 -o slice.jpg
-
-# From stdin
-cat track.mp3 | songsee - --format png -o out.png
-```
-
-## Visualization Types
-
-Use `--viz` with comma-separated values:
-
-| Type | Description |
-|------|-------------|
-| `spectrogram` | Standard frequency spectrogram |
-| `mel` | Mel-scaled spectrogram |
-| `chroma` | Pitch class distribution |
-| `hpss` | Harmonic/percussive separation |
-| `selfsim` | Self-similarity matrix |
-| `loudness` | Loudness over time |
-| `tempogram` | Tempo estimation |
-| `mfcc` | Mel-frequency cepstral coefficients |
-| `flux` | Spectral flux (onset detection) |
-
-Multiple `--viz` types render as a grid in a single image.
-
-## Common Flags
-
-| Flag | Description |
-|------|-------------|
-| `--viz` | Visualization types (comma-separated) |
-| `--style` | Color palette: `classic`, `magma`, `inferno`, `viridis`, `gray` |
-| `--width` / `--height` | Output image dimensions |
-| `--window` / `--hop` | FFT window and hop size |
-| `--min-freq` / `--max-freq` | Frequency range filter |
-| `--start` / `--duration` | Time slice of the audio |
-| `--format` | Output format: `jpg` or `png` |
-| `-o` | Output file path |
-
-## Notes
-
-- WAV and MP3 are decoded natively; other formats require `ffmpeg`
-- Output images can be inspected with `vision_analyze` for automated audio analysis
-- Useful for comparing audio outputs, debugging synthesis, or documenting audio processing pipelines