AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.
AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.
AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.
AI operational modes (brainstorm, implement, debug, review, teach, ship, orchestrate). Use to adapt behavior based on task type.
Orchestrates a dual-AI engineering loop where Claude Code plans and implements, while Codex validates and reviews, with continuous feedback for optimal code quality
Split work across subagents with explicit contracts, interfaces, and merge strategies. Use when parallelizing tasks, distributing workload, or orchestrating multi-agent workflows.
Orchestrates a triple-AI engineering loop where Claude plans, Codex validates logic and reviews code, and Cursor implements, with continuous feedback for optimal code quality
Patterns for building, maintaining, and scaling bioinformatics workflows. Covers Nextflow, Snakemake, WDL/Cromwell, container orchestration, and best practices for reproducible computational...
Patterns for building reliable background job processing systems. Covers message queues, worker pools, retries, dead letter handling, and async workflow orchestration. Use when ", " mentioned.
Orchestrates a full morning sweep of pending items (email, tasks, Slack, WhatsApp, X). Use when the user asks for a sweep, morning routine, inbox sweep, or all pending items.
Build LLM applications with LangChain and LangGraph. Use when creating RAG pipelines, agent workflows, chains, or complex LLM orchestration. Triggers on LangChain, LangGraph, LCEL, RAG, retrieval,...
Build LLM applications with LangChain and LangGraph. Use when creating RAG pipelines, agent workflows, chains, or complex LLM orchestration. Triggers on LangChain, LangGraph, LCEL, RAG, retrieval,...
Ultimate AGI-level autonomous agent with FULL MCP integration. Expert in multi-step reasoning, self-improvement, tool orchestration, and goal decomposition. Uses all 11 MCP servers for maximum capability.
Generate or update aramb.toml configuration file by analyzing docker-compose files or codebase. Use this skill when you need to create project metadata, service configurations, or environment...
Design and orchestrate multi-agent systems. Use when building complex AI systems requiring specialization, parallel processing, or collaborative problem-solving. Covers agent coordination,...
Guide for creating effective aramb skills. Use this skill when users want to create a new skill or update an existing skill that extends agent capabilities with specialized knowledge, workflows,...
Orchestrate multi-agent workflows where users watch each step in the overlay. Uses different CLI agents (cursor, pi, codex) for specialized roles with file-based handoff and auto-continue support...
Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js...
Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js...
Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js...