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v2.4: Ecosystem Edition - 2,545 triplets, 388 capabilities, 100% validation

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  1. README.md +27 -7
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@@ -66,7 +66,7 @@ widget:
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  <img src="https://img.shields.io/badge/Embedding-88.2%25-green" alt="Embedding Accuracy">
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  <img src="https://img.shields.io/badge/GGUF-Q4__K__M-blue" alt="GGUF">
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  <img src="https://img.shields.io/badge/Latency-<10ms-orange" alt="Latency">
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- <img src="https://img.shields.io/badge/Agents-13-cyan" alt="Agent Types">
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  <img src="https://img.shields.io/badge/License-Apache%202.0-green" alt="License">
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  </p>
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@@ -108,17 +108,25 @@ Using **hybrid keyword+embedding strategy** plus **contrastive fine-tuning**, Ru
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  | Embedding Only | 88.2% | 40.0% | +48.2 pts |
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  | **Keyword-First Hybrid** | **100.0%** | 95.0% | +5 pts |
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- ### Training Enhancements (v2.3)
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- - **1,078 training triplets** (578 base + 500 Claude-generated)
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- - **48% hard negative ratio** for better discrimination (up from 18%)
 
 
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  - **Claude Opus 4.5** used for generating confusing pairs
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  - **Triplet + InfoNCE loss** for contrastive learning
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  - **Real Candle training** with gradient-based weight updates
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- - **GRPO feedback loop** using Claude as judge
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- - **GGUF export** with adapter merging
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- ### Supported Agent Types (13)
 
 
 
 
 
 
 
 
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  | Agent | Keywords | Use Cases |
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  |-------|----------|-----------|
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  | `api-docs` | openapi, swagger, api spec | API documentation |
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  | `planner` | sprint, plan, roadmap | Project planning |
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  ---
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  ## 💰 Cost Savings
 
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  <img src="https://img.shields.io/badge/Embedding-88.2%25-green" alt="Embedding Accuracy">
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  <img src="https://img.shields.io/badge/GGUF-Q4__K__M-blue" alt="GGUF">
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  <img src="https://img.shields.io/badge/Latency-<10ms-orange" alt="Latency">
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+ <img src="https://img.shields.io/badge/Capabilities-388-cyan" alt="Capabilities">
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  <img src="https://img.shields.io/badge/License-Apache%202.0-green" alt="License">
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  </p>
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  | Embedding Only | 88.2% | 40.0% | +48.2 pts |
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  | **Keyword-First Hybrid** | **100.0%** | 95.0% | +5 pts |
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+ ### Training Enhancements (v2.4 - Ecosystem Edition)
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+ - **2,545 training triplets** (1,078 SOTA + 1,467 ecosystem)
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+ - **Full ecosystem coverage**: claude-flow, agentic-flow, ruvector
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+ - **388 total capabilities** across all tools
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+ - **62 validation tests** with 100% accuracy
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  - **Claude Opus 4.5** used for generating confusing pairs
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  - **Triplet + InfoNCE loss** for contrastive learning
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  - **Real Candle training** with gradient-based weight updates
 
 
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+ ### Ecosystem Coverage (v2.4)
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+
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+ | Tool | CLI Commands | Agents | Special Features |
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+ |------|--------------|--------|------------------|
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+ | **claude-flow** | 26 (179 subcommands) | 58 types | 27 hooks, 12 workers, 29 skills |
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+ | **agentic-flow** | 17 commands | 33 types | 32 MCP tools, 9 RL algorithms |
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+ | **ruvector** | 6 CLI, 22 Rust crates | 12 NPM | 6 attention, 4 graph algorithms |
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+
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+ ### Supported Agent Types (58+)
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  | Agent | Keywords | Use Cases |
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  |-------|----------|-----------|
 
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  | `api-docs` | openapi, swagger, api spec | API documentation |
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  | `planner` | sprint, plan, roadmap | Project planning |
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+ ### Extended Capabilities (v2.4)
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+
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+ | Category | Examples |
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+ |----------|----------|
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+ | **MCP Tools** | memory_store, agent_spawn, swarm_init, hooks_pre-task |
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+ | **Swarm Topologies** | hierarchical, mesh, ring, star, adaptive |
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+ | **Consensus** | byzantine, raft, gossip, crdt, quorum |
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+ | **Learning** | SONA train, LoRA finetune, EWC++ consolidate, GRPO optimize |
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+ | **Attention** | flash, multi-head, linear, hyperbolic, MoE |
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+ | **Graph** | mincut, GNN embed, spectral, pagerank |
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+ | **Hardware** | Metal GPU, NEON SIMD, ANE neural engine |
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+
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  ---
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  ## 💰 Cost Savings