Skill UI

This guide provides comprehensive patterns and best practices for designing high-impact Key Performance Indicator (KPI) dashboards. It covers everything from establishing a KPI framework (Strategic, Tactical, Operational) to defining departmental metrics (Sales, Marketing, Finance) and implementing best-practice layouts for executive summaries and SaaS metrics. Use this skill to translate raw data into actionable business insights.

This skill guides you through advanced integration patterns to connect Sentry with your full observability stack. Learn how to correlate error events from structured loggers (like Winston/Pino) using Event IDs, track business metrics (counters, gauges) within Sentry, and link performance data across multiple tools (Grafana, Datadog). Achieve end-to-end visibility, ensuring every error is tied back to its root cause and business context.

Build comprehensive 3-5 year financial models essential for startup planning and fundraising. This skill meticulously projects revenue using cohort-based methods, details cost structures (COGS, S&M, R&D, G&A), plans headcount, and performs detailed cash flow analysis. It calculates critical metrics like LTV, CAC, and burn rate, providing three scenarios (conservative, base, optimistic) for robust strategic decision-making.

This guide provides a comprehensive framework for early-stage companies to track, calculate, and optimize their key performance indicators (KPIs). It covers best practices for various startup business models, guiding teams from the initial seed stage through to Series A funding. Use this skill when developing, analyzing, or refining a structured startup metrics strategy.

Use the Recommendation Canvas to vet AI product concepts by mapping business and customer outcomes, hypotheses, positioning, risks, and success metrics so you can make defensible investment recommendations.

An expert guide for planning, designing, and implementing statistically rigorous A/B tests and product experiments. It covers core principles like formulating strong hypotheses, selecting primary/guardrail metrics, calculating sample sizes, and analyzing results to drive actionable business insights.

A comprehensive framework for preparing for high-stakes, adversarial board meetings, investor updates, or fundraising pitches. This guide teaches founders how to master key business metrics (MRR, burn rate, CAC/LTV) cold, anticipate the toughest questions, and structure an honest, confident narrative that maintains credibility even when presenting bad news.

A comprehensive toolkit for accelerating digital product growth. It covers essential strategies including growth hacking, SEO/ASO optimization, building viral loops, email marketing funnels, CRM implementation, and analyzing the entire customer acquisition lifecycle using AARRR metrics. Ideal for product managers and marketers aiming for exponential business expansion.

A systematic framework for launching and validating new products and business models. It guides users through the Build-Measure-Learn loop, emphasizing validated learning over vanity metrics, and structuring Minimum Viable Product (MVP) experiments to test core assumptions and determine if a pivot or perseverance is necessary.

This expert acts as a dedicated data analysis partner for Product Managers. It helps users explore data, write complex queries (e.g., SQL, BigQuery), analyze key metrics, and create structured dashboards. Use this tool when you need to derive actionable insights from complex datasets, compare user cohorts, or understand product performance trends to inform critical business decisions.

Generates a comprehensive, single-screen financial report in a self-contained HTML file. This skill is designed for analyzing key business metrics, including P&L summaries, MRR trends, KPI cards (Revenue, Gross Margin, Cash Runway), and top-accounts analysis. Ideal for quarterly or monthly financial reviews in SaaS or startup environments.

This guide provides a comprehensive framework for designing statistically rigorous A/B tests, split tests, and multivariate experiments. It covers everything from formulating strong hypotheses and calculating sample sizes to selecting appropriate primary, secondary, and guardrail metrics for various business contexts.