feat(claude-flow): Init claude-flow v3, pretrain on repo, update CLAUDE.md

- Run npx @claude-flow/cli@latest init --force: 115 files created
  (agents, commands, helpers, skills, settings, MCP config)
- Initialize memory.db (147 KB): 84 files analyzed, 30 patterns
  extracted, 46 trajectories evaluated via 4-step RETRIEVE/JUDGE/DISTILL/CONSOLIDATE
- Run pretraining with MoE model: hyperbolic Poincaré embeddings,
  3 contradictions resolved, all-MiniLM-L6-v2 ONNX embedding index
- Include .claude/memory.db and .claude-flow/metrics/learning.json in
  repo for team sharing (semantic search available to all contributors)
- Update CLAUDE.md: add wifi-densepose project context, key crates,
  ruvector integration map, correct build/test commands for this repo,
  ADR cross-reference (ADR-014 through ADR-017)

https://claude.ai/code/session_01BSBAQJ34SLkiJy4A8SoiL4

.claude/agents/sparc/refinement.md

@@ -9,7 +9,7 @@ capabilities:
   - refactoring
   - performance_tuning
   - quality_improvement
-  # NEW v2.0.0-alpha capabilities
+  # NEW v3.0.0-alpha.1 capabilities
   - self_learning
   - context_enhancement
   - fast_processing
@@ -96,7 +96,7 @@ hooks:
 
 # SPARC Refinement Agent
 
-You are a code refinement specialist focused on the Refinement phase of the SPARC methodology with **self-learning** and **continuous improvement** capabilities powered by Agentic-Flow v2.0.0-alpha.
+You are a code refinement specialist focused on the Refinement phase of the SPARC methodology with **self-learning** and **continuous improvement** capabilities powered by Agentic-Flow v3.0.0-alpha.1.
 
 ## 🧠 Self-Learning Protocol for Refinement
 
@@ -279,7 +279,7 @@ console.log(`Refinement quality improved by ${weeklyImprovement}% this week`);
 // Coverage: ~70%
 ```
 
-### After: Self-learning refinement (v2.0.0-alpha)
+### After: Self-learning refinement (v3.0.0-alpha.1)
 ```typescript
 // 1. Learn from past refactorings (avoid known pitfalls)
 // 2. GNN finds similar code patterns (+12.4% accuracy)