Results for “dst”

Interview an instructor and generate a complete MATLAB and Simulink enabled course in IMS Common Cartridge format. Use when the user asks to create a MATLAB course, Simulink course, MATLAB and Simulink curriculum, MATLAB Course Designer-ready course shell, Common Cartridge course package, .imscc export, MATLAB Exercises with validated .m files, or Simulink Exercises with starter and solution model files. Coordinates IDStack, MATLAB Agentic Toolkit, Simulink Agentic Toolkit, matlab-create-course-activity, simulink-create-course-activity, and the existing matlab-generate-grader-assessments skill.

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Symfony UX Map for interactive maps with Leaflet or Google Maps in Symfony. Covers markers, polygons, polylines, circles, info windows, and LiveComponent integration. Use when displaying maps, placing markers, drawing shapes or routes, handling map events, building store locators, using custom tile layers, or making maps reactive with LiveComponent. Code triggers: <twig:ux:map />, Map(), Point(), Marker(), Polygon(), Polyline(), Circle(), InfoWindow(), MapOptionsInterface, ComponentWithMapTrait, fitBoundsToMarkers, ux:map:marker:before-create, ux:map:connect, SYMFONY_UX_MAP_DSN. Also trigger when the user asks "how to display a map", "how to add markers", "how to draw a polygon on a map", "how to handle map click events", "how to make a reactive map", "how to use Leaflet in Symfony", "how to use Google Maps in Symfony", "map not showing", "map has zero height". Do NOT trigger for SVG icons (use ux-icons) or general frontend interactivity (use stimulus).

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Comprehensive Flow Nexus platform management - authentication, sandboxes, app deployment, payments, and challenges

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Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management

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Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.

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Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration

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

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Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory

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Implement semantic vector search with AgentDB for intelligent document retrieval, similarity matching, and context-aware querying. Use when building RAG systems, semantic search engines, or intelligent knowledge bases.

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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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Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

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

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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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SPARC (Specification, Pseudocode, Architecture, Refinement, Completion) comprehensive development methodology with multi-agent orchestration

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Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows

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Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.

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

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Create new Claude Code Skills with proper YAML frontmatter, progressive disclosure structure, and complete directory organization. Use when you need to build custom skills for specific workflows, generate skill templates, or understand the Claude Skills specification.

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Comprehensive GitHub code review with AI-powered swarm coordination

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Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.

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