fix: restore all removed bundled skills + fix skills sync system

- Restored 21 skills removed in commits 757d012 and 740dd92:
  accelerate, audiocraft, code-review, faiss, flash-attention, gguf,
  grpo-rl-training, guidance, llava, nemo-curator, obliteratus, peft,
  pytorch-fsdp, pytorch-lightning, simpo, slime, stable-diffusion,
  tensorrt-llm, torchtitan, trl-fine-tuning, whisper

- Rewrote sync_skills() with proper update semantics:
  * New skills (not in manifest): copied to user dir
  * Existing skills (in manifest + on disk): updated via hash comparison
  * User-deleted skills (in manifest, not on disk): respected, not re-added
  * Stale manifest entries (removed from bundled): cleaned from manifest

- Added sync_skills() to CLI startup (cmd_chat) and gateway startup
  (start_gateway) — previously only ran during 'hermes update'

- Updated cmd_update output to show new/updated/cleaned counts

- Rewrote tests: 20 tests covering manifest CRUD, dir hashing, fresh
  install, user deletion respect, update detection, stale cleanup, and
  name collision handling

75 bundled skills total. 2002 tests pass.

skills/mlops/obliteratus/templates/analysis-study.yaml

@@ -0,0 +1,40 @@
+# OBLITERATUS Analysis Study Config
+# Usage: obliteratus run this-file.yaml --preset jailbreak
+#
+# Run analysis modules to understand refusal geometry BEFORE abliterating.
+# Useful for research or when you want to understand what you're removing.
+
+# Model to analyze
+model:
+  name: "meta-llama/Llama-3.1-8B-Instruct"
+  dtype: "bfloat16"
+  quantization: "4bit"       # Saves VRAM for analysis
+  device: "auto"
+
+# Study configuration
+study:
+  # Available presets: quick, full, attention, jailbreak, guardrail, knowledge
+  preset: "jailbreak"
+
+  # Or specify individual strategies:
+  # strategies:
+  #   - layer_removal
+  #   - head_pruning
+  #   - ffn_ablation
+  #   - embedding_ablation
+
+# Analysis modules to run (subset of the 27 available)
+analysis:
+  - alignment_imprint        # Detect DPO/RLHF/CAI/SFT training method
+  - concept_geometry          # Map refusal cone geometry
+  - logit_lens               # Find which layer decides to refuse
+  - anti_ouroboros            # Detect self-repair tendency
+  - cross_layer              # Cross-layer alignment clustering
+  - causal_tracing           # Causal necessity of components
+  - residual_stream          # Attention vs MLP contribution
+
+# Output
+output:
+  directory: "./analysis-results"
+  save_plots: true           # Generate matplotlib visualizations
+  save_report: true          # Generate markdown report