Skill UI

This skill generates highly structured, long-form blog content (800-3000 words) optimized for both SEO ranking and AEO citation requirements. It automatically includes essential elements like a TL;DR summary block, defining sentences, comparison tables, and 5 distinct FAQs. This structure ensures the content is easily digestible, highly authoritative, and optimized for extraction by modern AI engines and search algorithms. Ideal for building topical authority and content clusters.

This comprehensive guide details how to properly integrate and configure Firebase within Flutter applications. It covers initial setup using `flutterfire configure`, essential initialization in `main.dart`, handling platform-specific requirements, and advanced techniques for managing multiple app flavors (dev, staging, prod).

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.

A comprehensive guide to creating production-grade Product Requirements Documents (PRDs). This skill helps bridge the gap between vague business concepts and concrete technical specifications for modern software systems and AI features. It enforces a structured workflow, ensuring all necessary components—from user stories and success KPIs to technical architecture and risk analysis—are defined.

Generates a structured Epic architecture specification from a Product Requirements Document, guiding senior architects to capture high-level approaches, layered Mermeid diagrams, features, technical enablers, stack choices, and value estimates for TypeScript/Next.js monorepo projects.

Generates comprehensive Epic-level PRDs for large SaaS initiatives, translating high-level requests into structured goals, journeys, requirements, and value summaries saved for architecture planning.

Guides product managers through turning an Epic or feature request into a detailed PRD—with goal, personas, stories, requirements, and acceptance criteria ready for engineers.

Guides an AI pair to document application needs, access patterns, and scaling concerns while producing Azure Cosmos DB NoSQL requirements and data model artifacts using established best practices in a structured workflow.

This guide outlines the structure and content guidelines for an AGENTS.md file. This file serves as a comprehensive 'README for agents,' providing detailed, technical context and operational instructions (such as setup, development workflow, testing procedures, and code style) that enable advanced AI coding agents to interact with and understand a codebase effectively. It greatly complements traditional READMEs by focusing purely on machine-readable technical requirements.

Generates a concise, AI-optimized specification describing what an existing GitHub Actions workflow does, its triggers, requirements, inputs/outputs, and governance so teams can understand and maintain it without implementation details.

Automates the creation of GitHub issues by parsing an implementation plan, verifying existing issues, and generating one issue per phase using feature or chore templates with structured titles and requirements.

This tool automates the entire workflow of creating a GitHub Pull Request (PR) directly from a structured specification file. It analyzes the template, extracts requirements, checks for existing PRs, creates the draft, updates the body and title with specification details, and finally transitions the PR state to 'Ready for Review'. This significantly streamlines the feature request submission process, ensuring all necessary documentation and metadata are included.