Skill UI

Provides durable workflow automation guidance for AI agents, covering platforms like n8n, Temporal, Inngest and patterns such as sequential, parallel, and orchestrator-worker flows to turn brittle scripts into production-grade orchestration.

A comprehensive guide covering patterns and architectures for automating code execution using LLMs. It spans simple sequential pipelines (e.g., daily dev scripts) to advanced, RFC-driven multi-agent Directed Acyclic Graph (DAG) orchestration. Ideal for building CI/CD style continuous development pipelines, managing complex state, and automating quality gates without human intervention.

A robust framework for orchestrating complex, multi-step coding tasks using multiple AI agents. It functions by first planning the entire project into a mission dependency graph (DAG), then dispatching specialized agents to isolated Git worktrees for parallel development. The system automatically monitors progress, handles merges, and generates structured, comprehensive reports detailing changes, completed tasks, and next steps.

AgentFlow transforms your existing Kanban board (Asana, GitHub, Linear) into a self-managing, autonomous AI development pipeline. It orchestrates multiple AI agents through defined stages (Backlog to Done), enforcing deterministic quality gates, performing adversarial reviews, and tracking costs—all visible within your existing project management UI. It provides crash-proof execution and full observability for complex software development lifecycles.

A comprehensive guide for creating, updating, refactoring, and reviewing solutions built on the Microsoft Agent Framework. This skill provides unified best practices for both .NET and Python environments, serving as a modern successor to Semantic Kernel and AutoGen. It emphasizes adherence to the latest official documentation, async patterns, robust error handling, and structured agent/workflow orchestration for complex AI applications.

This tool allows users to execute complex, multi-agent workflows defined in YAML format directly within the AI environment. It functions as an orchestration engine, sequentially invoking various specialized roles (agents) without requiring manual API key configuration. Ideal for structured tasks requiring collaboration between multiple personas.

A comprehensive minimal terminal coding harness designed for building, extending, and integrating advanced AI capabilities directly into CLI environments. It supports deep integration via SDK (Node/TypeScript), RPC, and JSON event streams. Developers can create custom skills, providers, TUI components, and utilize advanced features like web search, video understanding, and agent orchestration.