Skill UI

This tool searches the current repository and lists all pull requests assigned to the user. It provides comprehensive details for each PR, including its purpose and scope. The output is highly functional, highlighting pending review status, detailing any failed checks (with suggested fixes), and offering to automatically request a Copilot review to maintain continuous development flow. Ideal for daily workflow status checks.

A comprehensive guide to configuring complex nodes in workflow automation platforms like n8n. Learn best practices for understanding operation-specific field requirements, managing property dependencies, and utilizing progressive disclosure techniques (Standard vs. Full detail) to ensure accurate and efficient workflow setup.

This guide provides proven architectural patterns for building complex, reliable, and scalable workflows using n8n. It covers core patterns like Webhook processing, HTTP API integration, database synchronization, AI agent design, and scheduled tasks. Learn how to select the right pattern and utilize advanced components for robust automation.

Guides creation or updates of object-oriented component documentation by analyzing code or existing docs, then applying C4/Arc42/IEEE templates to capture architecture, interfaces, and quality traits.

Automates Outlook mail, calendar, contacts, folders, and attachments through the Rube MCP-powered Composio toolkit, letting you orchestrate KQL/OData searches and event/contact management once connections and tool schemas are established.

A structured methodology for coordinating multiple, simultaneous investigation threads to determine the root cause of complex system failures, performance regressions, or integration bugs. This skill decomposes a large problem into independent tracks (e.g., database, application code, infrastructure), assigns ownership, and manages structured sync points (Continue/Pivot/Converge) to converge on a solution faster than serial debugging. Essential for high-stakes production incident response.

The Phoenix CLI is a powerful tool for debugging complex LLM and agent workflows. It allows users to fetch detailed traces, spans, and sessions, analyze errors, and structure findings using open and axial coding techniques. It is essential for investigating complex LLM failures, building robust failure taxonomies, and guiding the next steps in application evaluation after initial instrumentation.

Phoenix Evals lets teams build evaluators for AI/LLM apps by wiring deterministic code with LLM nuance, running Python or TypeScript workloads, validating against humans, and iterating through error analysis, RAG, and production workflows.

Guides hooking Phoenix AI services with OpenInference tracing, covering setup, spans, instrumentation, and production deployment for LLM workflows using Python or TypeScript.

This tool generates a complete, production-ready PHP Model Context Protocol (MCP) server project. It automatically scaffolds the entire structure, including tools, resources, prompts, and comprehensive tests, utilizing the official PHP SDK. It provides a standardized, robust starting point for developers building AI-integrated backend services in PHP.

This skill implements a file-based planning system (Manus style) for managing complex, multi-step projects. It uses persistent Markdown files—including `task_plan.md`, `progress.md`, and `findings.md`—as structured, disk-based working memory. It is ideal for maintaining context, conducting detailed project analysis, tracking progress across long sessions, and ensuring continuity even after interruptions.

A file-based system designed to organize and track the progress of complex, multi-stage tasks, perfect for extensive research or detailed project development. It uses persistent Markdown files (task_plan.md, progress.md, findings.md) as a 'desktop memory' to maintain state and context across sessions. Supports automatic session recovery and structured workflow tracking, making it invaluable for large-scale, multi-tool usage projects.