Skill UI

Master advanced state management using Riverpod in Flutter and Dart. This guide covers setting up providers, defining different provider types (Future, Stream), utilizing reactive reading (ref.watch) and one-time access (ref.read), handling lifecycles, combining providers, and implementing proper testing strategies. Learn best practices for building scalable and maintainable Flutter applications.

A comprehensive skill for the entire lifecycle of AI capability development. Use this tool to draft new skills from scratch, iteratively improve existing ones, and rigorously measure their performance. The process includes capturing user intent, defining test cases, running quantitative benchmarks, evaluating results, and optimizing the skill description for maximum triggering accuracy.

Spec-Driven Development (SDD) is a structured methodology that mandates defining comprehensive specifications before writing any code. It guides users through a gated process: SPECIFY -> PLAN -> TASKS -> IMPLEMENT. This workflow ensures all assumptions are surfaced, requirements are concrete, and the final product has clear success criteria, minimizing ambiguity and architectural risk in large projects.

This skill enables the generation of high-quality, cinematic videos using a highly structured prompt format (JSON). Users define detailed cinematic elements—including background, characters, camera movements, dialogue, and audio—and can optionally provide a reference image to guide the visual style or content of the final output. It automates the complex AIGC video generation workflow.

Defines a systematic, multi-phase research methodology that prioritizes broad exploration, targeted deep dives, and validation before initiating any content generation, ensuring reliable, multi-angle web intelligence.

This skill guides the creation and editing of Obsidian Bases (.base files). It enables users to build dynamic, database-like views of notes by applying complex filters (AND, OR, NOT), defining computed properties using formulas, and configuring multiple views (table, cards, list). Use this when you need to aggregate, filter, or summarize information across multiple notes in a structured way, simulating a lightweight, navigable knowledge database.

This skill provides comprehensive management for annotation schemas (configs) and human review workflows (queues) within the Arize platform. It supports defining categorical, continuous, and freeform label types. Users can programmatically apply these annotations to project spans and datasets using the Python SDK, facilitating structured human feedback loops and improving model monitoring.

This guide teaches how to build well-structured and robust ASP.NET Minimal APIs. It covers best practices for API organization, defining clear DTOs with proper validation, handling strongly-typed parameters, and leveraging modern C# features. Crucially, it demonstrates how to generate comprehensive, standards-compliant OpenAPI/Swagger documentation using built-in .NET features, ensuring APIs are fully documented for seamless consumption.

This advanced prompt simulates a Senior Project Manager and DevOps specialist. It takes comprehensive feature artifacts (PRD, technical breakdowns, testing plans) and generates a structured, automated GitHub project plan. It enforces Agile best practices (Epic > Feature > Story > Enabler > Task) and includes templates for issue creation, dependency management, risk assessment, and Definition of Done, ensuring robust project tracking within GitHub.

This tool analyzes specification files to extract all defined requirements and cross-references them with the current codebase implementation status. It systematically checks for unimplemented features, searches existing GitHub issues to prevent duplicates, and automatically generates detailed issues using a standardized feature request template. It is essential for robust product management, ensuring every defined requirement is tracked and scheduled for development.

This document defines the strict, mandatory structure and deterministic rules for creating implementation plans. It ensures that plans for new features, refactoring, or architectural changes are fully self-contained, machine-readable, and structured for automated execution by advanced AI agents or human teams.

This comprehensive guide provides a structured set of prompts to manage the entire lifecycle of upgrading a legacy .NET solution. It covers everything from initial project classification and dependency compatibility review to code modernization (e.g., async conversion), updating CI/CD pipelines, and defining robust testing and deployment strategies. Ideal for large-scale migration of older .NET applications to modern frameworks like .NET 8.