Set up a Docker container for running Nextflow training examples. Handles basic setup, Docker-outside-of-Docker (DooD) for containerized processes, ARM Mac platform emulation, and troubleshooting. Use when you need to run Nextflow examples in a consistent environment.
Walk through a training tutorial as a user would, progressively building examples exactly as instructed, running all commands, and verifying results against solutions. Use when testing tutorials end-to-end or validating that instructions are correct and complete.
Run comprehensive validation and review checks including heading numbering, TODO/FIXME comments, Nextflow script conventions, orphaned files, admonition syntax, lesson structure, formatting, content accuracy, and teaching effectiveness. Use when validating, reviewing, or checking training materials quality, lesson quality, or before committing changes.
Validate authorization failures including IDOR, privilege escalation, and missing access controls. Test by attempting unauthorized access with lower-privileged credentials. Use when testing CWE-639 (IDOR), CWE-269 (Privilege Escalation), CWE-862 (Missing Authorization), CWE-863 (Incorrect Authorization), CWE-284 (Access Control), CWE-285 (Improper Authorization), or CWE-425 (Direct Request/Forced Browsing) findings.
Verify that hl_lines attributes in markdown code blocks correctly highlight the intended lines. Use when reviewing documentation with code examples, especially Before/After comparisons, or when highlights seem incorrect.
Stop a running MkDocs preview server. Use when port 8000 is busy, switching tasks, or done editing documentation.
Add an interactive exercise with solution to an existing lesson. Creates properly formatted exercise and solution admonition blocks. Use when a lesson needs hands-on practice.
Create a new numbered lesson page within an existing training module. Use when adding a new topic like '05_error_handling.md' to an existing course.
Scaffold a complete new training module with standard directory structure, index, orientation, lessons, survey, and next-steps files. Use when creating a new course like 'Advanced Pipelines' or a new domain module.
Finding and accessing AI/LLM model brand icons from lobe-icons library. Use when users need icon URLs, want to download brand logos for AI models/providers/applications (Claude, GPT, Gemini, etc.), or request icons in SVG/PNG/WEBP formats.
Enables a secondary AI model to advise the primary when it gets stuck, fails repeatedly, or needs upfront planning.
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.
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.
Comprehensive GitHub release orchestration with AI swarm coordination for automated versioning, testing, deployment, and rollback management
Cloud-based AI swarm deployment and event-driven workflow automation with Flow Nexus platform
Multi-repository coordination, synchronization, and architecture management with AI swarm orchestration
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.
Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
