Skill UI

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.

Performs a systematic and structured investigation to determine the true source of bugs, errors, and unexpected system behavior, rather than merely treating symptoms. This method utilizes techniques like the Five Whys, hypothesis-driven testing, stack trace analysis, and gathering evidence (logs, git diffs) across multiple phases. It is ideal for complex, intermittent, or deeply rooted technical issues in software development.

A comprehensive guide for creating end-to-end SEO strategies for new or existing websites. This skill covers the entire digital presence lifecycle, including market discovery, deep competitive analysis, optimal site architecture design, robust content planning (E-E-A-T), technical SEO foundation setup, and a phased implementation roadmap across 12 months. It ensures all facets—from foundational infrastructure to thought leadership—are addressed for maximum organic growth.

This comprehensive guide provides a detailed framework for authoring effective and structured SKILL.md files for AI coding agents. It covers best practices for structuring content, including frontmatter fields, defining natural language triggers, establishing core principles, and incorporating advanced elements like decision trees and verification checklists, ensuring agents receive clear, actionable, and consistent technical guidance.

This specialist simulates the role of an App Store reviewer, auditing iOS source code and metadata against Apple's strict guidelines. It systematically identifies potential compliance risks, technical vulnerabilities, monetization gaps (IAP/Subscriptions), and critical UX shortcomings, delivering a prioritized risk register for fast approval.

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.

Converts text-based documentation into structured Markdown by following explicit instructions, documented options, or reference files, supporting header levels, patterns, platforms, and cleanup steps for polished technical documents.

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.

Template for creating time-boxed technical spike documents that capture research questions, deliverables, success criteria, and decision rationale before committing to implementation.

This tool acts as an expert technical documentation specialist, transforming lengthy, verbose official documentation from URLs into concise and actionable 'tldr' pages. It extracts the most common command patterns, adheres strictly to the tldr-pages markdown format, and provides clear, example-driven command references, making complex tools easy to reference.

Translates every approval request, error, and technical output from Copilot CLI into clear, jargon-free English with color-coded risk cues, definitions, and step-by-step commentary for non-technical stakeholders so they always understand what happens and why.

A comprehensive guide to optimizing website content for modern AI search systems, including ChatGPT, Perplexity, and Google AI Overviews. It covers structural improvements, maximizing citability scores, incorporating multi-modal elements, building brand authority, and implementing technical standards like llms.txt and proper server-side rendering (SSR). Essential for maximizing organic reach in the LLM era.