Skill UI

This skill provides comprehensive tools to download, export, and deeply inspect existing Arize traces and spans. It is essential for understanding the full execution flow of complex LLM applications, debugging runtime errors, and performing root-cause analysis. Users can retrieve detailed data filtered by Trace ID, Span ID, or Session ID, enabling thorough analysis of conversational or multi-step agent behaviors.

Conducts a multistep preflight validation for Azure Bicep deployments, covering syntax checks, what-if previews, permission verification, and report generation so teams can confidently run azd or az deployments with known outcomes.

This comprehensive guide provides a complete, step-by-step workflow for setting up a modern Spring Boot Java project from scratch. It covers downloading the project template, configuring multiple data sources (PostgreSQL, Redis, MongoDB), integrating API documentation (SpringDoc), and orchestrating a full, containerized service environment using Docker Compose. Ideal for complex, enterprise-level application development.

A sophisticated, file-based system designed for organizing and tracking complex, multi-step projects. It utilizes structured Markdown files (task_plan.md, progress.md, findings.md) to maintain a complete record of plans, research findings, and progress updates. Ideal for project analysis, workflow management, and ensuring data integrity throughout the planning lifecycle.

This skill generates a detailed, multi-phase plan for complex, multi-file refactoring projects. It ensures safety by first analyzing the codebase, identifying dependencies, and structuring changes in a safe sequence (e.g., Types first, then implementations, followed by tests and cleanup). It forces the AI to output a comprehensive plan, including rollback steps and verification points, and waits for user confirmation before making any actual code changes.

This skill is designed to manage complex, multi-step tasks by coordinating the efforts of multiple specialized AI agents. It provides structured methods for listing available agents, initiating real-time conversations, submitting complex background tasks (such as data analysis or report generation), tracking task status, and maintaining conversational context using session IDs. It is essential when a core task requires diverse expert knowledge or sequential collaboration.

A comprehensive automation skill for managing core business processes within the Square ecosystem. It enables users to list, monitor, cancel payments, search and update customer orders, manage business locations, and handle invoices. Designed for complex, multi-step workflows, ensuring robust handling of parameters, versioning, and pagination for reliable commercial operations.

This advanced agent acts as a highly constrained implementation expert, designed to execute complex, multi-step plans with absolute fidelity. It strictly adheres to the provided workflow, making only specified changes, updating the plan status in real-time, and running tests until completion. Ideal for disciplined software development, detailed project execution, or formal process adherence.

Process videos, audio, images, and documents on Transloadit’s cloud using 86+ robots to encode formats, generate thumbnails, resize/watermark, run OCR, speech-to-text, moderation, and chain multi-step pipelines for scalable media automation.

A comprehensive skill designed to convert vague ideas, initial concepts, or high-level requirements into structured, detailed, and approved technical specifications. It enforces a rigorous, multi-step workflow, guiding users through context exploration, proposing multiple architectural trade-offs, and iteratively refining the design until a complete specification document is ready for the implementation phase.

This technique guides users on how to solve highly complex questions that require tracking a chain of related entities (e.g., Author -> Article -> Mentioned Person). Instead of attempting a single search, the process must be broken down into sequential steps, using the result of one search as an anchor point for the next, thereby building a comprehensive knowledge chain.

This skill is designed for scenarios requiring complex, multi-step task decomposition. Instead of asking an Agent to perform the task directly, it guides the process of requesting a clear, actionable, sequential execution plan from a stronger Agent. The core function emphasizes that the user must execute the generated plan themselves, ensuring the output is a roadmap, not a final answer.