rUv

Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning

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Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.

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15-agent hierarchical mesh coordination for v3 implementation. Orchestrates parallel execution across security, core, and integration domains following 10 ADRs with 14-week timeline.

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Complete security architecture overhaul for claude-flow v3. Addresses critical CVEs (CVE-1, CVE-2, CVE-3) and implements secure-by-default patterns. Use for security-first v3 implementation.

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Achieve aggressive v3 performance targets: 2.49x-7.47x Flash Attention speedup, 150x-12,500x search improvements, 50-75% memory reduction. Comprehensive benchmarking and optimization suite.

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Choose and validate RuVector or AgentDB memory for an agent application, including provenance, isolation, retention and workload-specific retrieval benchmarks.

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Discover and integrate RuV Stack projects when the user asks where to begin with ruvnet, which RuV tools fit a goal, or how the stack fits together.

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Generate or evolve a repository-specific CLI, MCP and skills harness using MetaHarness, with bounded evaluation and explicit release authority.

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Connect to x.ruv.io, read federation channels and claims, or coordinate authorized work across Ruflo hosts with explicit identity and publishing boundaries.

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Evaluate proposed repository harness changes with pinned Darwin tools and explicit evidence limits.

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Turn a feature request into a minimal, file-level implementation plan before any code.

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Inspect repository session replay and verify configured MetaHarness field memory boundaries before reusing outcomes.

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Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning

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Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform

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Advanced GitHub Actions workflow automation with AI swarm coordination, intelligent CI/CD pipelines, and comprehensive repository management

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Orchestrate multi-agent swarms with agentic-flow for parallel task execution, dynamic topology, and intelligent coordination. Use when scaling beyond single agents, implementing complex workflows, or building distributed AI systems.

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Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.

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Comprehensive GitHub code review with AI-powered swarm coordination

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Comprehensive performance analysis, bottleneck detection, and optimization recommendations for Claude Flow swarms

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Train and deploy neural networks in distributed E2B sandboxes with Flow Nexus

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AI-assisted pair programming with multiple modes (driver/navigator/switch), real-time verification, quality monitoring, and comprehensive testing. Supports TDD, debugging, refactoring, and learning sessions. Features automatic role switching, continuous code review, security scanning, and performance optimization with truth-score verification.

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Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows

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Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.

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Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre/post task hooks, session management, Git integration, memory coordination, and neural pattern training for enhanced development workflows.

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