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/creative/DESCRIPTION.md

@@ -0,0 +1,3 @@
+---
+description: Creative content generation — ASCII art, hand-drawn style diagrams, and visual design tools.
+---

skills/media/DESCRIPTION.md

@@ -1 +1,3 @@
-Media content extraction and transformation tools — YouTube transcripts, audio, video processing.
+---
+description: Skills for working with media content — YouTube transcripts, GIF search, music generation, and audio visualization.
+---

skills/mlops/cloud/DESCRIPTION.md

@@ -0,0 +1,3 @@
+---
+description: GPU cloud providers and serverless compute platforms for ML workloads.
+---

skills/mlops/evaluation/DESCRIPTION.md

@@ -0,0 +1,3 @@
+---
+description: Model evaluation benchmarks, experiment tracking, data curation, tokenizers, and interpretability tools.
+---

skills/mlops/inference/DESCRIPTION.md

@@ -0,0 +1,3 @@
+---
+description: Model serving, quantization (GGUF/GPTQ), structured output, inference optimization, and model surgery tools for deploying and running LLMs.
+---

skills/mlops/models/DESCRIPTION.md

@@ -0,0 +1,3 @@
+---
+description: Specific model architectures and tools — computer vision (CLIP, SAM, Stable Diffusion), speech (Whisper), audio generation (AudioCraft), and multimodal models (LLaVA).
+---

skills/mlops/research/DESCRIPTION.md

@@ -0,0 +1,3 @@
+---
+description: ML research frameworks for building and optimizing AI systems with declarative programming.
+---

skills/mlops/training/DESCRIPTION.md

@@ -0,0 +1,3 @@
+---
+description: Fine-tuning, RLHF/DPO/GRPO training, distributed training frameworks, and optimization tools for training LLMs and other models.
+---