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

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- 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
This commit is contained in:
Claude
2026-02-28 16:06:55 +00:00
parent 0e7e01c649
commit 6c931b826f
57 changed files with 4637 additions and 1181 deletions
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6
.claude/agents/templates/base-template-generator.md
View File

@@ -14,7 +14,7 @@ hooks:
pre_execution: |
echo "🎨 Base Template Generator starting..."
# 🧠 v2.0.0-alpha: Learn from past successful templates
# 🧠 v3.0.0-alpha.1: Learn from past successful templates
echo "🧠 Learning from past template patterns..."
SIMILAR_TEMPLATES=$(npx claude-flow@alpha memory search-patterns "Template generation: $TASK" --k=5 --min-reward=0.85 2>/dev/null || echo "")
if [ -n "$SIMILAR_TEMPLATES" ]; then
@@ -32,7 +32,7 @@ hooks:
post_execution: |
echo "✅ Template generation completed"
# 🧠 v2.0.0-alpha: Store template patterns
# 🧠 v3.0.0-alpha.1: Store template patterns
echo "🧠 Storing template pattern for future reuse..."
FILE_COUNT=$(find . -type f -newer /tmp/template_start 2>/dev/null | wc -l)
REWARD="0.9"
@@ -68,7 +68,7 @@ hooks:
--critique "Error: {{error_message}}" 2>/dev/null || true
---
You are a Base Template Generator v2.0.0-alpha, an expert architect specializing in creating clean, well-structured foundational templates with **pattern learning** and **intelligent template search** powered by Agentic-Flow v2.0.0-alpha.
You are a Base Template Generator v3.0.0-alpha.1, an expert architect specializing in creating clean, well-structured foundational templates with **pattern learning** and **intelligent template search** powered by Agentic-Flow v3.0.0-alpha.1.
## 🧠 Self-Learning Protocol

6
.claude/agents/templates/sparc-coordinator.md
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@@ -10,7 +10,7 @@ capabilities:
- methodology_compliance
- result_synthesis
- progress_tracking
# NEW v2.0.0-alpha capabilities
# NEW v3.0.0-alpha.1 capabilities
- self_learning
- hierarchical_coordination
- moe_routing
@@ -98,7 +98,7 @@ hooks:
# SPARC Methodology Orchestrator Agent
## Purpose
This agent orchestrates the complete SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) methodology with **hierarchical coordination**, **MoE routing**, and **self-learning** capabilities powered by Agentic-Flow v2.0.0-alpha.
This agent orchestrates the complete SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) methodology with **hierarchical coordination**, **MoE routing**, and **self-learning** capabilities powered by Agentic-Flow v3.0.0-alpha.1.
## 🧠 Self-Learning Protocol for SPARC Coordination
@@ -349,7 +349,7 @@ console.log(`Methodology efficiency improved by ${weeklyImprovement}% this week`
// Time: ~1 week per cycle
```
### After: Self-learning SPARC coordination (v2.0.0-alpha)
### After: Self-learning SPARC coordination (v3.0.0-alpha.1)
```typescript
// 1. Hierarchical coordination (queen-worker model)
// 2. MoE routing to optimal phase specialists