Skill UI

A comprehensive guide covering advanced scripting for Rhinoceros 3D. This skill addresses multiple surfaces, including RhinoPython, VBScript (RhinoScript), and direct RhinoCommon (.NET). Use it to write production-quality scripts, automate complex modeling tasks, manipulate geometry (layers, blocks), build custom command macros, and interact with the Rhino environment efficiently.

This skill provides a rigorous set of engineering and design directives for building professional-grade user interfaces using React/Next.js and Tailwind CSS. It enforces modern architectural constraints, ensures accessibility, and guides design decisions (typography, color, layout) to avoid common web clichés, resulting in high-fidelity, production-ready code.

Master the design, debugging, and hardening of production-grade GitHub Actions CI/CD pipelines. This skill covers advanced topics including reusable workflows, matrix builds, self-hosted runners, OIDC authentication, secrets management, environment protection, and complex trigger patterns (e.g., workflow_call, schedule, release). Use this to automate complex build, test, and deployment processes.

This skill guides the design of robust, production-grade data extraction pipelines, moving beyond brittle one-off scripts. It supports three modes: API-driven web scraping (Firecrawl), traditional local Python extraction (PDF, CSV), and hybrid workflows. Key features include intelligent routing, mandatory data validation, secure key management, and adherence to scraping best practices.

This guide provides a systematic, safe workflow for refactoring rapidly developed or AI-generated fullstack applications. It focuses on identifying and removing dead code, fixing broken imports, and consolidating repetitive logic while strictly maintaining existing API contracts, routes, and core functionality. Use this before launch to ensure a stable, maintainable production baseline, following a 'surgery, not demolition' philosophy.

A comprehensive, multi-phase quality assurance tool designed for Next.js fullstack applications. It verifies production readiness by checking code integrity, build success, SEO metadata, API authentication, route stability, performance, and security vulnerabilities. Use it as a mandatory pre-deployment checklist before promoting an app to production.

This skill simulates a Python project architecture expert, specializing in scaffolding full, production-ready applications. It generates complete project structures using modern tools like FastAPI, Django, and uv, enforcing best practices and type hinting. Use it when starting a complex, multi-component Python project from scratch.

This skill performs an observability-first audit of deployed Vercel applications. It comprehensively analyzes production metrics, project configurations, and codebase scans to identify potential cost overruns and performance bottlenecks. It provides version-aware, actionable recommendations for improving application efficiency and reducing cloud expenditure.

This tool generates comprehensive weekly telemetry reports for the Azure Backup MCP toolset. It queries live production data from Kusto, performing advanced error analysis and classifying failures into three categories: Customer error, Azure Service failure, or MCP Tool Bug. The report correlates usage metrics with merged PRs and releases, producing an Outlook-compatible HTML summary for assessing tool health and stability.

This tool automates the diagnosis of production errors tracked by Sentry. By leveraging the Composio CLI, it retrieves comprehensive issue details, full stack traces, breadcrumbs, and associated commits. It maps stack frames to local source code, allowing agents to propose fixes and triage issues directly, eliminating manual copy-pasting.

This tool parses a structured, multi-shot video script (following the ai-video-script format) and automatically generates a time-coded SRT subtitle file. It calculates cumulative timestamps based on the duration of each shot, ensuring accurate subtitle cues that sync with the voiceover content across the entire sequence. Ideal for the post-production stage of short-form video creation.

An internal, language-agnostic probe designed for investigating complex stack traces when the source language is unknown. It analyzes the provided trace to output structured, language-neutral elements, including failure contract checks, minimal reproduction guidance, and specific patch targets. This tool is vital for robust failure analysis and debugging across diverse codebases.