chore: update claude-flow v3 init configuration#160
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…l coherence ## Learning Module (src/learning/mod.rs) - ReasoningBank for pattern storage with similarity lookup and pruning - TrajectoryTracker ring buffer for task execution tracking - Spike-driven attention for 87x energy efficiency (based on Yao et al.) - Multi-head attention for distributed task routing - NetworkLearning unified interface for edge nodes ## RAC Module (src/rac/mod.rs) - Adversarial Coherence Thesis Implements the 12 axioms for browser-scale adversarial truth maintenance: 1. Connectivity is not truth 2. Everything is an event 3. No destructive edits (deprecation only) 4. Every claim is scoped 5. Semantics drift is expected 6. Disagreement is signal 7. Authority is scoped, not global 8. Witnesses matter 9. Quarantine is mandatory 10. All decisions are replayable 11. Equivocation is detectable 12. Local learning is allowed Core components: - Append-only Merkle event log for tamper-evident history - CoherenceEngine for conflict detection and resolution - QuarantineManager for contested claims - Authority policy and verifier traits - Decision traces for audit and replay ## Integration - Learning and RAC integrated into EdgeNetNode - 28 tests pass (13 new tests for learning/RAC) References: - FLP Impossibility (MIT CSAIL) - PBFT Byzantine Fault Tolerance - CRDTs (Lip6) - RFC 6962 Certificate Transparency 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Security audit identified 5 CRITICAL, 10+ HIGH severity issues - Added 85 passing tests: adversarial scenarios, economic edge cases, RAC axioms - Added economics module for RAC sustainability and treasury management - Enhanced learning module with self-learning intelligence - Fixed hooks configuration (--silent → 2>/dev/null || true) Key security findings: - CRITICAL: Weak PBKDF in Pi-Key (SHA-256 only, needs Argon2id) - CRITICAL: Private key exposure via export_secret_key - CRITICAL: Signature verification unimplemented in RAC - HIGH: Session key derivation weakness - HIGH: No memory zeroization for sensitive data Architecture assessment: ~60% production ready (B+ rating) All 85 tests pass: 18 adversarial + 38 economic + 29 RAC axioms 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Critical security fixes before production deployment: 1. Argon2id PBKDF in pikey/mod.rs (replaces SHA-256) - Memory-hard KDF with 64MB memory, 3 iterations - Version 0x02 format with salt, backward compatible with v1 - Secure zeroization of key material 2. Ed25519 signature verification in rac/mod.rs - Real cryptographic verification for authority resolutions - ScopedAuthority::sign_resolution() helper for signing - Canonical message format for verification 3. Password-protected key export in identity/mod.rs - export_secret_key now requires 8+ character password - AES-256-GCM encryption with Argon2id-derived key - import_secret_key for secure recovery Dependencies added: - argon2 v0.5 (memory-hard KDF) - zeroize v1.7 (secure memory cleanup) Test coverage: - 125 tests passing (40 lib + 85 integration) - Updated adversarial tests with real Ed25519 signatures 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
WASM Packages (published to npm as @ruvector/*): - learning-wasm (39KB): MicroLoRA rank-2 adaptation with <100us latency - economy-wasm (182KB): CRDT-based autonomous credit economy - exotic-wasm (150KB): NAO governance, Time Crystals, Morphogenetic Networks - nervous-system-wasm (178KB): HDC, BTSP, WTA, Global Workspace - attention-unified-wasm (339KB): 18+ attention mechanisms (Neural, DAG, Graph, Mamba) Changes: - Add ruvector-attention-unified-wasm crate with unified attention API - Add ruvector-economy-wasm crate with CRDT ledger and reputation - Add ruvector-exotic-wasm crate with emergent AI mechanisms - Add ruvector-learning-wasm crate with MicroLoRA adaptation - Add ruvector-nervous-system-wasm crate with bio-inspired components - Fix ruvector-dag for WASM compatibility (feature flags) - Add exotic AI capabilities to edge-net example - Update README with WASM documentation - Include pkg/ directories with built WASM bundles 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
…ages Enhanced documentation for all 5 WASM packages: - learning-wasm: MicroLoRA architecture, zero-allocation examples, benchmarks - economy-wasm: CRDT explanation, contribution curves, stake/slash mechanics - exotic-wasm: NAO governance, morphogenetic networks, time crystal coordination - nervous-system-wasm: HDC operations, BTSP one-shot learning, WTA/K-WTA, Global Workspace - attention-unified-wasm: 18+ mechanisms across Neural/DAG/Graph/SSM categories All READMEs include: - NPM badges (version, license, bundle size, WebAssembly) - TypeScript/JavaScript code examples - Performance benchmarks in tables - API reference tables - SEO keywords for npm discoverability 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Enable capabilities module with pub export - Add compute/ module with SIMD, WebGPU, WebGL backends - Add ai/ module with attention, router, federated learning, LoRA - Streamline WASM API for Time Crystal, NAO, MicroLoRA, HDC, WTA, BTSP - Add Global Workspace and Morphogenetic network support - Add learning scenarios for error recovery and file sequences - Add swarm collective intelligence and consensus modules 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Four attention mechanisms answering fundamental questions: - Neural Attention: What words/tokens matter? - DAG Attention: What computational steps matter? - Graph Attention: What relationships matter? - State Space: What history still matters? Includes: - dag_attention.rs: Critical path analysis, topological ordering - attention_unified.rs: Unified interface composing all 4 types - Updated mod.rs architecture diagram 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Build WASM module (1.1MB compressed) - Create CLI with commands: start, benchmark, info, demo - Fix symbol collisions (RacEconomicEngine, RacSemanticRouter) - Security review passed: - Zeroize for secret cleanup - OsRng for cryptographic randomness - Argon2 for password hashing - AES-GCM authenticated encryption Package: https://www.npmjs.com/package/@ruvector/edge-net Usage: npx @ruvector/edge-net info npx @ruvector/edge-net demo 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
…-system-wasm - Implement comprehensive tests for adaptive learning mechanisms including MicroLoRA and SONA in learning_tests.rs. - Introduce tests for bio-inspired neural components such as HDC, BTSP, and Spiking Neural Networks in nervous_system_tests.rs. - Create common utilities for random vector generation, vector assertions, and softmax calculations in mod.rs. - Ensure all tests validate expected behaviors and maintain numerical stability.
- Build dual WASM targets (web + nodejs) for universal compatibility - Add Node.js polyfills for web APIs (crypto, performance, window, document) - Create universal entry point with auto-detection of environment - Update CLI with comprehensive benchmark, demo, and info commands - Fix ESM/CJS compatibility with .cjs extension for Node.js module - Package includes both browser and Node.js WASM binaries Published to npm as @ruvector/edge-net v0.1.1 Package: 885.4 kB compressed, 3.2 MB unpacked 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
feat(edge-net): Distributed Compute Intelligence Network with WASM
Built from commit 71907b2 Platforms updated: - linux-x64-gnu - linux-arm64-gnu - darwin-x64 - darwin-arm64 - win32-x64-msvc 🤖 Generated by GitHub Actions
Complete ViteJS dashboard implementation with: - HeroUI components for responsive mobile/desktop layout - Time Crystal dark theme with crystal, temporal, quantum colors - Network stats visualization with real-time canvas animation - CDN integration panel for WASM/AI/crypto script management - WASM modules panel with status and benchmark tracking - MCP tools panel with 15 default swarm/neural/performance tools - Credits economy panel with time crystal staking - Browser console debug panel with log capture - Zustand stores for state management - React Query for async data - Docker configuration (multi-stage nginx build) - Comprehensive test suite (39 tests passing) Dashboard features: - Responsive sidebar (desktop) and drawer (mobile) navigation - Tab-based content switching with framer-motion animations - Real-time network activity simulation - Debug console with timing utilities and window.edgeNet API - Glow effects and crystal-themed visual styling 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Built from commit 27cd7ae Platforms updated: - linux-x64-gnu - linux-arm64-gnu - darwin-x64 - darwin-arm64 - win32-x64-msvc 🤖 Generated by GitHub Actions
…consent UI - Add EdgeNet service with real WASM module initialization from CDN - Add PiKey cryptographic identity store with Ed25519 signatures - Add IndexedDB persistence for credits, tasks, and settings - Add ConsentWidget for CPU/GPU contribution with settings modal - Add IdentityPanel for crypto identity management - Add DocumentationPanel with comprehensive user guide - Add SpecializedNetworks component for network communities - Deploy Edge-Net Genesis Relay to Google Cloud Run with security: - Origin validation (CORS whitelist) - Rate limiting (100 msgs/min per node) - Message size limits (64KB) - Connection timeout (30s heartbeat) - Max 5 connections per IP - Update Header with Edge-Net branding - Update Sidebar with Docs tab - Update networkStore to use real WASM stats - Configure dashboard to connect to Genesis relay 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
…al intelligence Implements a privacy-preserving financial learning system that runs entirely in the browser using WebAssembly. Key features: - PlaidLocalLearner: Browser-local ML engine with IndexedDB persistence - Q-learning for budget optimization and spending recommendations - HNSW vector index for semantic transaction categorization - Spiking neural network for temporal pattern recognition - Anomaly detection for unusual transaction flagging - Zero data exfiltration - all learning stays client-side Components: - examples/edge/src/plaid/mod.rs: Core Rust learning algorithms - examples/edge/src/plaid/wasm.rs: WASM bindings for browser - examples/edge/pkg/plaid-local-learner.ts: TypeScript API wrapper - examples/edge/pkg/plaid-demo.html: Interactive demo page - examples/edge/docs/plaid-local-learning.md: Comprehensive documentation Privacy guarantees: - Financial data never leaves the browser - Optional AES-256-GCM encryption for IndexedDB storage - User can delete all data instantly - No analytics, telemetry, or tracking
…g verification Implements ZK proofs that allow users to prove financial statements without revealing actual numbers. Key features: - Bulletproofs-style range proofs (no trusted setup required) - Pedersen commitments to hide actual values - Proof types: income, affordability, savings, overdraft, debt ratio - Complete rental application proof bundle - All proof generation runs in browser WASM Components: - examples/edge/src/plaid/zkproofs.rs: Core ZK proof system - examples/edge/src/plaid/zk_wasm.rs: WASM bindings for browser - examples/edge/pkg/zk-financial-proofs.ts: TypeScript API - examples/edge/pkg/zk-demo.html: Interactive demo Use cases: - Rental applications: Prove income ≥ 3× rent without revealing salary - Loan pre-qualification: Prove DTI ratio without revealing debts - Employment verification: Prove minimum salary without exact pay - Account stability: Prove no overdrafts without transaction history Privacy guarantee: Verifier mathematically CANNOT extract actual numbers from the proof - only learns whether statement is true or false.
Security Fixes: - Remove blinding factor from Commitment struct (was leaking secrets) - Add per-installation unique salt for key derivation (was hardcoded) - Add prominent security warnings to zkproofs.rs (demo-only crypto) - Document that ZK implementation is for API demonstration only Performance Fixes: - Fix memory leak: category_embeddings now uses HashMap instead of Vec - Add LRU-style eviction at 10k embeddings capacity - Prevents unbounded memory growth that would crash browser Code Quality: - Add max_embeddings configuration option - Better documentation for data structures - Add security audit report and optimization guides⚠️ IMPORTANT: The ZK proof cryptography is simplified for demonstration. For production use, replace with bulletproofs, curve25519-dalek, merlin crates.
…ial proofs - Add production crypto: bulletproofs 5.0, merlin 3.0, subtle 2.5, lazy_static - Implement zkproofs_prod.rs with real Ristretto255 Pedersen commitments - Add constant-time operations via subtle crate for side-channel resistance - Create zk_wasm_prod.rs with WASM bindings for browser-based ZK proofs - Fix bit size calculation (Bulletproofs requires power-of-2: 8, 16, 32, 64) - Fix memory leak: use rand crate instead of getrandom for non-wasm Security improvements: - Real cryptographic Bulletproofs (not demo hashing) - Fiat-Shamir transcripts via Merlin for non-interactive proofs - Constant-time comparison to prevent timing attacks - Proof expiration and integrity verification All 7 production ZK tests pass.
… proofs Security Fixes: - CRITICAL: Add zeroize on drop for FinancialProver to prevent memory extraction - HIGH: Fix WASM type import (ProdVerificationResult -> VerificationResult) - MEDIUM: Add input validation for zero rent/multiplier/budget values - Use checked_mul instead of saturating_mul for overflow detection Performance Optimizations: - Reduce generator memory from 16 MB to 8 MB (1-party vs 16-party) - Add zeroize dependency (1.8) for secure memory clearing Documentation: - Add comprehensive ZK performance analysis docs - Add benchmark suite for criterion testing - Add optimization quick reference and examples All 7 production ZK tests pass.
Built from commit 74ba07f Platforms updated: - linux-x64-gnu - linux-arm64-gnu - darwin-x64 - darwin-arm64 - win32-x64-msvc 🤖 Generated by GitHub Actions
- Add join.js CLI for joining EdgeNet with public key identity - Support generating new Pi-Key identities with Ed25519 signing - Enable encrypted identity export/import (Argon2id + AES-256-GCM) - Add multi-contributor demonstration and cross-verification - Update main CLI to include join command - Fix test file syntax errors and assertion bounds - All 186 Rust tests pass, WASM module fully functional
- Implement PersistentIdentity class for months/years persistence - Store identities in ~/.ruvector/identities with encrypted backup - Track contribution history in ~/.ruvector/contributions - Add --list command to show all stored identities - Add --history command to show contribution milestones - Auto-restore identities across sessions - Track "return after absence" milestones (>30 days) - Session tracking with timestamps - Add multi-contributor-test.js for network simulation - All contributions preserved indefinitely
- Add network.js with peer discovery, QDAG contribution ledger, and contribution verification protocol - Add join.html for browser-based network joining with Web Crypto API - Update join.js with NetworkManager integration for QDAG recording - Add --peers and --network commands for network status viewing - Update package.json with new files and scripts The QDAG (Quantum DAG) ledger provides: - Contribution recording with parent selection for DAG structure - Weight-based confirmation (3 confirmations for finality) - Peer-to-peer synchronization support (simulated in local mode) - Contributor statistics and network-wide metrics The browser join page provides: - WASM-based Pi-Key identity generation - PBKDF2 + AES-256-GCM encrypted identity backup/restore - Real-time contribution tracking and credit display - localStorage persistence for cross-session identity
Security improvements (v0.1.86-87): - Add NEURAL_CONSTANTS with 27 named constants replacing magic numbers - Add NeuralLogger interface with configurable logging (no more console.warn) - Add readonly modifiers to interface properties for immutability - Add input validation: ID length, content length, embedding dimensions - Add resource limits: MAX_MEMORIES=10000, MAX_AGENTS=1000, MAX_DRIFT_EVENTS=1000 - Add stale agent cleanup in EmbeddingStateMachine (1hr timeout) - Add cluster detection limits to prevent O(n²) DoS (MAX_CLUSTER_AGENTS=500) - Add zero-vector handling in cosine similarity - Fix reflex error handling with graceful degradation Performance optimizations (v0.1.88): - LRUCache: O(1) get/set/evict with doubly-linked list + hash map (2x faster) - Float32BufferPool: Pre-allocated buffer reuse (17x faster, 100% reuse) - TensorBufferManager: Named working buffers for intermediate computations - VectorOps: 8x loop unrolling for dot/distance (1.3-1.5x faster) - VectorOps: 4x unrolling + local vars for cosine (1.6x faster) - ParallelBatchProcessor: Chunked concurrent processing - OptimizedMemoryStore: Combined LRU cache + buffer pool Benchmark results: - Buffer Pool: 0.06 µs vs 1.03 µs (17x improvement) - LRU Cache eviction: O(1) vs O(n) - Cosine similarity: 0.39 µs vs 0.61 µs (1.6x improvement) - Memory store search: 703 µs vs 1301 µs (2x improvement) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
…ge networks - Add networks.js with NetworkGenesis, NetworkRegistry, and MultiNetworkManager - Support for public, private (invite-only), and consortium networks - Each network has its own genesis block, QDAG ledger, and peer registry - Network IDs derived from genesis hash for tamper-evident identity - Invite code generation for private networks with base64url encoding New CLI options: --networks List all known networks --discover Discover available networks --create-network Create a new network with custom name/type --network-type Set network type (public/private/consortium) --switch Switch active network for contributions --invite Provide invite code for private networks Security features: - Network isolation with separate storage per network - Cryptographic network identity from genesis hash - Invite codes for access control on private networks - Ed25519 signatures for network announcements Well-known networks: - mainnet: Primary public compute network - testnet: Testing and development network
…nhancements Analysis module: - Add complexity analysis (cyclomatic, cognitive, Halstead metrics) - Add security scanning (SQL injection, XSS, command injection detection) - Add pattern detection (code smells, design patterns) Workers module: - Add native worker implementation for parallel processing - Add benchmark worker for performance testing - Add worker type definitions Core improvements: - Add adaptive embedder with dynamic model selection - Add ONNX optimized embeddings with caching - Update intelligence engine with enhanced learning - Update parallel workers with better concurrency Dashboard enhancements: - Add relay client service for Edge-Net communication - Update network stats and specialized networks components - Update network store with improved state management - Update type definitions Configuration: - Add custom workers skill - Add agentic-flow and ruvector fast scripts - Update settings and gitignore 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
feat(dashboard): Edge-Net Time Crystal Dashboard
Adds comprehensive README documenting the 6-stage CRV signal line methodology mapping to ruvector subsystems. Bumped to v0.1.1. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
docs: Add ADR-017 and DDD for Craftsman Ultra 30b 1bit BitNet integration
Built from commit 35bc22c Platforms updated: - linux-x64-gnu - linux-arm64-gnu - darwin-x64 - darwin-arm64 - win32-x64-msvc 🤖 Generated by GitHub Actions
Built from commit 8664582 Platforms updated: - linux-x64-gnu - linux-arm64-gnu - darwin-x64 - darwin-arm64 - win32-x64-msvc 🤖 Generated by GitHub Actions
Built from commit 87e0a40 Platforms updated: - linux-x64-gnu - linux-arm64-gnu - darwin-x64 - darwin-arm64 - win32-x64-msvc 🤖 Generated by GitHub Actions
- Workspace version: 2.0.1 → 2.0.2 - ruvector-sona: 0.1.4 → 0.1.5 (adds Debug impl for SonaEngine) - ruvllm: 2.0.2 (BitNet integration from PR #151) Published crates: - ruvector-sona v0.1.5 - ruvllm v2.0.2 Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Added: - ruvector-temporal-tensor: Temporal tensor store with tiered quantization - ruvector-crv: CRV signal line protocol for vector search - BitNet 1.58-bit quantization features to ruvllm description Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Added ADR links (018-023) and DDD reference for: - Block-based storage engine - Tiered quantization formats - Temporal scoring tier migration - Delta compression reconstruction - WASM API cross-platform - Benchmarking acceptance criteria Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
feat: Add quantum simulation engine ADR series (QE-001 to QE-012) and DDD design documents
Built from commit d9072d8 Platforms updated: - linux-x64-gnu - linux-arm64-gnu - darwin-x64 - darwin-arm64 - win32-x64-msvc 🤖 Generated by GitHub Actions
Published crates: - ruqu-core v2.0.2 - State-vector simulator - ruqu-algorithms v2.0.2 - VQE, Grover, QAOA, Surface Code - ruqu-exotic v2.0.2 - Quantum-classical hybrids - ruqu-wasm v2.0.2 - WebAssembly bindings Updated README with quantum engine section linking ADRs: - QE-001 to QE-012: Core architecture to MinCut coherence - Code example for GHZ state creation Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Built from commit 9ce325e Platforms updated: - linux-x64-gnu - linux-arm64-gnu - darwin-x64 - darwin-arm64 - win32-x64-msvc 🤖 Generated by GitHub Actions
Built from commit ea5d9b6 Platforms updated: - linux-x64-gnu - linux-arm64-gnu - darwin-x64 - darwin-arm64 - win32-x64-msvc 🤖 Generated by GitHub Actions
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Crates.io (v2.0.3): - ruqu-core: High-performance quantum circuit simulator - ruqu-algorithms: VQE, Grover, QAOA, Surface Code - ruqu-exotic: Quantum-classical hybrid algorithms - ruqu-wasm: WebAssembly bindings npm (@ruvector/ruqu-wasm v2.0.3): - Browser-native quantum simulation - 25-qubit support with 105KB WASM bundle - TypeScript definitions included SEO-optimized READMEs with: - Performance benchmarks - API documentation - Code examples - ADR links Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Built from commit 6c6ded2 Platforms updated: - linux-x64-gnu - linux-arm64-gnu - darwin-x64 - darwin-arm64 - win32-x64-msvc 🤖 Generated by GitHub Actions
Aligns npm package version with crates.io release. Updates platform dependencies to match. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- ruvllm: Add missing keywords, categories, readme field - ruvector-sona: Fix docs.rs URL (was "sona", now "ruvector-sona") - ruvector-crv: Add badges, installation, related crates - graph-wasm npm: Add npm and license badges Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
…ance Install @claude-flow/memory as local dependency to enable the auto-memory bridge that was silently skipping. Update settings.json with Agent Teams hooks (TeammateIdle, TaskCompleted), SessionStart/End memory sync, and verified v3 configuration. Add operational guidance to CLAUDE.md covering disk space management, upgrade procedures, and health check reference. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Built from commit a9fdd88 Platforms updated: - linux-x64-gnu - linux-arm64-gnu - darwin-x64 - darwin-arm64 - win32-x64-msvc 🤖 Generated by GitHub Actions
4D Gaussian splatting demo deployed to Cloud Run at ruvector-vwm-875130704813.us-central1.run.app - football.html: Patriots vs Seahawks with 4000+ gaussians/frame, ESPN-style scorebug, 5 camera modes, play simulation engine, particle effects, atmospheric fog, post-processing pipeline - canvas-viewer.html: Canvas2D fallback for generic VWM viewing - Dockerfile + nginx.conf: Cloud Run deployment config Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Built from commit 724d003 Platforms updated: - linux-x64-gnu - linux-arm64-gnu - darwin-x64 - darwin-arm64 - win32-x64-msvc 🤖 Generated by GitHub Actions
Re-initialized claude-flow with --force to update agent configs, helpers, settings, and skills for DNA analyzer swarm orchestration. https://claude.ai/code/session_01QJhN7RNDnEHTPRVn9fMM2X
Initial draft from swarm agent covering three-regime gate selection based on El-Hayek, Khanna, and Abboud arXiv papers for dynamic min-cut, hypergraph sparsification, and Gomory-Hu trees. https://claude.ai/code/session_01QJhN7RNDnEHTPRVn9fMM2X
Comprehensive architecture design for the world's fastest DNA analyzer,
produced by a 15-agent hierarchical-mesh swarm. Documents include:
ADR Documents:
- ADR-018: DNA Analyzer Specification & DDD Architecture
- ADR-024: Deployment Architecture & Platform Strategy
- ADR-028: Graph Genome Min-Cut, Neural Intelligence, Vector Search, Security
- ADR-029: Self-Optimizing Nervous System (SONA)
DDD Domain Models:
- Epigenomics, CRISPR Engineering, Population Genomics, Pharmacogenomics
Grounded in three 2025 arXiv papers:
- El-Hayek et al.: Deterministic fully-dynamic min-cut (n^{o(1)} updates)
- Khanna et al.: Near-optimal hypergraph sparsification sketches
- Abboud et al.: Almost-linear-time Gomory-Hu trees
https://claude.ai/code/session_01QJhN7RNDnEHTPRVn9fMM2X
…chmarks, tests - ADR-018 specification: add information-theoretic bounds, TDA, quantum-inspired algorithms - Fix compile errors in ruvector-sparse-inference-wasm (9 errors resolved) - Fix compile error in ruvector-fpga-transformer (BackendSpec::as_ref) - Add HNSW genomic benchmarks (criterion) with real DNA k-mer workloads - Add min-cut genome graph benchmarks - Add real integration tests for core HNSW and min-cut (no mocks) - Add ruvector-dna-bench crate for real genomic data benchmarking https://claude.ai/code/session_01QJhN7RNDnEHTPRVn9fMM2X
ADR SOTA Enhancements (8 ADRs optimized): - ADR-018 DDD: event sourcing, CQRS, saga patterns, hexagonal architecture - ADR-028 Graph Genome: spectral sparsification, persistent homology, graph neural diffusion, expander decomposition - ADR-028 Neural: state space models (Mamba/S4), ring attention, KAN, mixture-of-depths, speculative decoding - ADR-028 Vector Search: DiskANN, RaBitQ, Matryoshka embeddings, ACORN filtered search, learned indexes - ADR-028 Security: post-quantum crypto (Kyber/Dilithium), TFHE, SPDZ MPC, Renyi DP, Plonk/Halo2 - ADR-029 SONA: progressive nets, lottery tickets, hypernetworks, PackNet, MAML meta-learning, NAS - ADR-024 Deployment: WebGPU, WebNN, confidential computing, unikernels, edge TPU, RISC-V RVV - DDD-003 Epigenomics: single-cell multi-omics, TADs, methylation clocks, 4D nucleome Code Quality (compile fixes + optimization): - Fix warnings across ruvector-mincut, ruvllm, sona crates - Optimize workspace Cargo.toml profiles (release, bench, release-with-debug) - Reduce unused imports, dead code, type mismatches Real DNA Benchmarks & Tests (no mocks): - Benchmark suite: HNSW genomic, min-cut graph, attention, delta propagation, quantization - Integration tests: core HNSW, min-cut, delta, SONA adaptation, Flash Attention - Real DNA analysis pipeline example with NCBI public sequences (PhiX174, SARS-CoV-2, E.coli, human mito) - Download script for public benchmark data from NCBI Deliverables: - Comprehensive README with comparison tables, QuickStart, collapsible guides - Security audit report - Performance optimization report https://claude.ai/code/session_01QJhN7RNDnEHTPRVn9fMM2X
Add complete DNA analysis pipeline with 2-bit packed sequence encoding, k-mer extraction, FASTA/FASTQ parsing, k-mer frequency embeddings, genomic vector search, variant calling with coherence gating, and staged pipeline orchestration. Fix ruvector-gnn-wasm native compilation by gating WASM-only bindings behind cfg(target_arch = "wasm32"). Modules: - sequence: 2-bit packed DNA (4x memory reduction), reverse complement - kmer: O(1) sliding window k-mer iterator, canonical forms - fasta: FASTA/FASTQ parser with N-base filtering - embedding: k-mer frequency + random projection to 384-dim vectors - search: brute-force cosine similarity index with taxonomy filtering - variant: SNP detection with isolation-based coherence gating - pipeline: staged parse -> QC -> embed -> search -> call pipeline https://claude.ai/code/session_01QJhN7RNDnEHTPRVn9fMM2X
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Re-initialized claude-flow with --force to update agent configs,
helpers, settings, and skills for DNA analyzer swarm orchestration.
https://claude.ai/code/session_01QJhN7RNDnEHTPRVn9fMM2X