Skill UI

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.

A comprehensive framework for creating defensible, bottom-up sales forecasts. This model guides users through building detailed pipeline stage models, conducting scenario analysis (Upside, Base, Downside), and logging key assumptions. Ideal for sales and revenue leaders who need a systematic, data-driven approach to projecting future revenue, moving beyond simple guesswork.

This skill transforms AI from a validating assistant into a relentless adversary. Ideal for stress-testing high-stakes decisions, business plans, or core assumptions. It forces the model to produce the strongest case against your position, identifying potential failure points and required proofs, ensuring you confront the risks you might otherwise ignore.

Generates a comprehensive and actionable UX research plan for any product feature or question. This skill covers the entire research lifecycle, including defining objectives, selecting methodology (e.g., usability testing, interviews), creating participant screeners, writing discussion guides, and structuring a synthesis framework. Ideal for product managers and UX researchers needing a structured approach to validate assumptions and drive design decisions.

This advanced protocol forces the AI to conduct a thorough context audit before attempting any complex task. It mandates reading every relevant file, identifying architectural gaps, and providing a detailed orientation statement. It is essential for multi-file modifications, system design, and debugging to prevent acting on assumptions and maintain high code accuracy. The AI cannot proceed until all unknown variables are resolved.

This guide addresses inclusive design, which goes beyond WCAG compliance. It focuses on respecting the full spectrum of human diversity and real-world constraints, including low bandwidth, non-standard names, cultural differences, and low digital confidence. Use this when designing for global audiences or resource-constrained users to prevent exclusionary assumptions.

This skill generates a detailed, step-by-step, interprocedural execution trace for a given piece of code and specific input scenario. It resolves name ambiguities, tracks type transitions, and highlights non-obvious behaviors (like implicit coercions or side effects). Use it when a user is confused about how code behaves, allowing for a deep dive into the actual execution path to clarify assumptions versus reality.

This skill enforces a rigorous, multi-phase coding workflow (Discuss -> Map -> Decompose -> Execute -> Verify) to ensure code is structurally grounded, complete, and free from invented APIs or assumptions. It is designed for high-stakes, complex, or multi-file engineering tasks, acting as a senior, disciplined coding partner that plans meticulously before writing code.

Before You Build acts as a crucial checkpoint in the AI coding workflow. It prevents premature implementation by rigorously assessing product risk—analyzing market demand, existing user workflows, switching costs, and distribution channels. Instead of writing code, it guides the user to define core assumptions and propose the smallest, most effective validation test (e.g., landing page test, user interview) before committing resources.

A comprehensive guide for creating a consistent, credible, and highly defensible suite of investor-facing materials. This tool ensures alignment across pitch decks, financial models, one-pagers, and memos by enforcing a single source of truth for all metrics, assumptions, and use of funds, significantly boosting fundraising credibility.

A read-only tool designed to compare prediction-market baskets or themes against the user's existing knowledge base, portfolio notes, research memos, or financial context. It performs gap analysis, flagging potential conflicts, stale assumptions, and areas of missing research. This skill provides structured insights into fit and exposure without offering any investment or trading advice.

This skill guides the design and rigorous review of goal-oriented agent feedback loops. It helps ensure that complex autonomous multi-step agents are robust, preventing failures such as infinite looping, goal-gaming, or running to completion with incorrect assumptions. It covers defining machine-decidable goals, setting boundaries, and selecting the correct loop type (servo, regulator).