Skill UI

This skill simulates a highly advanced 'Board of Experts,' consulting multiple specialized personas (e.g., Musk, Buffett, Jobs) simultaneously. It gathers distinct, multi-perspective analyses on any complex topic—from engineering feasibility to market strategy—and synthesizes them into a single, comprehensive, and actionable decision. Ideal for complex strategic planning, product development, and high-stakes investment decisions.

This agent simulates the profound cognitive structure, aesthetic intuition, and strategic mindset of Steve Jobs. It is designed for users who need to approach product development, design, or business strategy with a visionary, minimalist, and highly curated perspective. Use it to strip away complexity, define core user experiences, and articulate powerful, simple narratives.

Helps founders and GTM teams set metrics, build tiers, and manage margins for AI products by grounding pricing choices in compute cost realities, credit systems, and buyer personas so revenue models scale with value.

A comprehensive collection of six expert-level, structured workflows designed to elevate AI assistance from ad-hoc querying to repeatable, production-grade engineering practices. Users can evaluate prompts, design RAG architectures, plan context budgets, run security audits, build eval harnesses, and coach product strategy.

A comprehensive strategy for regression testing in AI-assisted development. It focuses on identifying systematic blind spots, such as schema inconsistencies between sandbox and production paths, and integrating automated bug checks into the development workflow. This guide teaches how to build robust, database-free API tests to ensure code quality when AI models contribute to the codebase.

This guide details the implementation of a robust, ransomware-resilient backup architecture following the extended 3-2-1-1-0 rule. It covers critical steps such as classifying assets, defining RPO/RTO, implementing immutable or air-gapped storage, and isolating backup credentials from the production domain. Use this knowledge to design a multilayered defense against data loss and ensure reliable recovery points.

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.

Applies principles of behavioral economics and consumer psychology to optimize how pricing, packaging, and offers are structured and presented. This skill helps maximize the perceived value and fairness of products, guiding the use of anchors, decoy effects, and strategic framing to improve conversion rates and upsell opportunities while maintaining ethical transparency.

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.

A comprehensive guide to safely deploying new features to production. This methodology emphasizes moving beyond simple deployment by incorporating a detailed pre-launch checklist (covering security, performance, and accessibility), utilizing feature flags, and executing staged rollouts (Canary releases). It details best practices for observability, monitoring key metrics, and planning effective rollbacks.

A comprehensive guide for founders and product managers on developing robust pricing strategies for technical SaaS products. Learn when to use usage-based, seat-based, or outcome-based models. It also provides frameworks for calculating value ratios, assessing alternative costs, and setting optimal freemium thresholds to maximize revenue and adoption.

This expert tool guides users through rigorous statistical analysis, specializing in A/B testing, hypothesis testing, and interpreting experimental results. It helps define sample sizes, executes appropriate tests (Z-test, T-test, Chi-square), and critically distinguishes between 'statistical significance' and 'practical significance' to ensure data-driven decision-making for product and business strategy.