Skill UI

This tool provides comprehensive competitive intelligence by scraping and analyzing data from major online platforms, including Google Maps, Booking.com, Facebook, Instagram, YouTube, and TikTok. It extracts structured data on competitors' content, pricing, ad strategies, review sentiment, and market positioning. Ideal for market researchers, product managers, and marketing strategists who need deep benchmarks across multiple digital channels to refine their own strategy.

A comprehensive tool for scraping e-commerce platforms to extract critical business data. Users can monitor product pricing, track competitor offers, analyze customer reviews for sentiment, and discover seller intelligence across various marketplaces. Ideal for market research, competitive analysis, and brand monitoring.

Generate a structured company profile that captures executive strategy quotes, product direction, transformation initiatives, and org dynamics for interview prep, competitive intelligence, partnerships, or market-entry planning.

Helps product managers diagnose whether AI workflows rely on indiscriminate context stuffing or deliberate context engineering, then apply bounded domains, retrieval, and Research→Plan→Reset→Implement practices to improve reliability and output quality.

Creates assumption-based proto personas from available research, market signals, and stakeholder insights to align teams early in product development and surface validation gaps.

This comprehensive skill guides you through the entire content lifecycle, from initial research and competitive analysis to drafting a full piece and finally performing SEO optimization. It ensures the output is a structured, authoritative, and publish-ready article, perfect for marketing teams creating technical blogs, guides, or long-form content.

This powerful orchestrator coordinates the entire product development lifecycle by routing inquiries across 16 specialized sub-skills (e.g., RICE, OKRs, UX research, analytics). It acts as a central hub for both deterministic task routing and running continuous, machine-gated discovery loops. Use it when you need to systematically prioritize features, run A/B tests, or drive a goal from initial assumption to validated repository code.

This agent provides structured summarization for academic papers, reports, and articles. It goes beyond simple summarizing by extracting key findings, generating comparative matrices across multiple sources, and producing properly formatted citations (APA, IEEE, etc.). It is designed for analysts, product managers, and researchers who need actionable, deep insights from dense documentation.

This expert guides users through comprehensive customer research, whether analyzing existing assets (transcripts, surveys, tickets) or gathering new intel from online sources (Reddit, G2, forums). It helps uncover deep customer pains, desired outcomes, and underlying needs (Jobs to Be Done) to ground product strategy, marketing copy, and positioning in real-world evidence.

This skill applies the Jobs To Be Done (JTBD) framework from behavioral economics. Instead of merely listing features, it helps uncover the underlying functional, emotional, and social progress a customer is trying to achieve when they 'hire' a product or service. It is essential for deep user research, defining product messaging, optimizing the user journey, and understanding the triggers that cause a customer to switch solutions.

This skill generates a comprehensive keyword strategy by identifying high-value SEO and AEO question queries for any given topic. It structures keywords into three difficulty tiers (T1, T2, T3), performs cannibalization checks to prevent content overlap, and builds a complete content map, guiding users on content type and production order for maximum search engine visibility.

This skill automates the process of transforming high-level product specifications, requirements, and design documents into a detailed, actionable, and executable task plan. It follows a multi-stage workflow, including context loading, parallel research, and two rigorous review gates (Task Plan Review and Task-Graph Sanity Review). The output provides properly sized (1-3 hours), logically sequenced tasks, ensuring every requirement is covered and dependencies are explicitly managed, dramatically improving project planning accuracy.