Skill UI

This comprehensive canvas guides teams through developing robust AI-powered features. It ensures product decisions are rigorous by covering problem definition, model selection (LLM, RAG, etc.), data governance, evaluation metrics, user experience design (including fallbacks), and responsible AI compliance. Ideal for assessing AI readiness and preventing common product failures.

Produces a comprehensive and structured change management plan for any organizational transformation or system rollout. This skill guides users through critical phases, including stakeholder analysis, impact assessment, communication strategy, training plan development, and resistance mitigation, ensuring a high probability of successful adoption.

This skill monitors key competitors across various signals (Product, Pricing, Hiring, Partnerships) and translates raw data into structured, actionable intelligence briefs. It assesses the strategic implications of competitor moves relative to your current roadmap, providing high/medium/low priority signals, recommended actions, and a concise strategic summary. Ideal for weekly competitive landscape monitoring and strategic planning.

This skill transforms scattered competitive updates (features, pricing, hiring, partnerships) into structured strategic intelligence. It assesses the threat level, determines whether a move is reactive or proactive, and provides concrete implications and actionable recommended responses directly tied to your product roadmap and business strategy.

This skill generates a comprehensive, data-driven Customer Health Scorecard for any account. It assesses renewal risk, expansion potential, and overall account vitality by scoring five key dimensions: Product Adoption, Engagement, Outcomes, Support Health, and Commercial status. The output provides a weighted score (out of 100) and a RAG status (Red, Amber, Green), guiding Customer Success Managers and leadership on immediate risks and recommended actions.

This skill generates a comprehensive customer journey map, detailing the entire customer experience from initial awareness through to advocacy. It identifies key stages, customer actions, emotional highs and lows, critical pain points, and actionable opportunities for product improvement or service enhancement. Ideal for UX research, product discovery, and cross-functional alignment.

A comprehensive framework for structuring deep-dive product data analysis, including funnel analysis, metric triage, and cohort studies. This guide forces the analyst to answer four critical questions: What changed, Why did it change, What is the impact, and What should we do next, ensuring insights lead directly to actionable business recommendations.

This skill generates a comprehensive discovery call brief designed for sales professionals. Users input prospect details and product info, and the AI outputs a structured guide including market research summaries, hypotheses about pain points, deep-dive questioning frameworks, and clear success criteria. It ensures every sales conversation is strategic, context-driven, and leads to a defined next step.

Transforms verbose, detailed product updates into highly concise and structured executive briefings. Ideal for C-suite reporting, board updates, or leadership summaries, this skill focuses on actionable insights: key metrics, risks, required decisions, and next steps, ensuring the information is immediately digestible for busy executives.

This comprehensive skill applies industry-standard prioritization frameworks, including RICE, MoSCoW, Kano, and ICE, to rank product features and backlog items. It generates a scored, defensible list that includes a recommended build order, explicitly deprioritized items, and documented assumptions. Essential for Product Managers and teams needing to make data-driven, strategic decisions about the product roadmap and manage scope trade-offs.

This skill automates a structured Product Management (PM) design review process. It assesses a Figma design against defined product requirements (PRD) and user flows, ensuring functional completeness and readiness for engineering handoff. It checks for requirements coverage, handles edge cases (empty/error/loading states), identifies functional concerns (not aesthetic), and provides a clear, actionable approval status.

Transforms complex financial model outputs (P&L, balance sheet figures) into clear, structured, and compelling written narratives. Ideal for preparing board packs, investor updates, or executive management reports by translating mere numbers into actionable stories. The output provides headline insights, detailed driver analysis, variance explanations, and robust forward-looking commentary tailored to specific audiences.