Skill UI

A structured framework based on the Cynefin model to classify problems by their underlying cause-effect domain (Clear, Complicated, Complex, Chaotic). It guides users on selecting the correct response mode and methodology before attempting solutions, preventing failure due to domain mismatch. Useful when unsure how to approach novel or mixed problems.

A strategic framework for making decisions when facing extreme uncertainty and unclear outcomes. Effectuation instructs users to start with available means (skills, assets, network) and define an affordable loss limit. Progress is driven by taking small, controlled actions to gain real commitments and information, allowing the ultimate goal to emerge naturally.

This robust methodology guides users to strip away assumed constraints, industry conventions, or historical precedents. By isolating only the fundamental, independently supported primitives (like physics, core math, or measured needs), it enables the rebuilding of the simplest, most robust solution that genuinely satisfies real-world constraints, bypassing artificial or arbitrary limitations.

This advanced methodology builds an evidence-linked causal chain from a localized fault to an actionable systemic root. It moves beyond simple proximate causes by requiring counterfactual testing, verifying multiple independent pathways, and prescribing countermeasures that eliminate enabling conditions, ensuring true recurrence prevention.

A strategic framework used in product management to shift focus from features to the core progress users are trying to achieve. It helps teams understand why users 'hire' a solution, map the forces driving change, and prioritize product development based on the true job needing completion, rather than just existing feature lists. Ideal for analyzing low adoption or defining new product strategy.

A rigorous methodology for systematic problem diagnosis and consequential decision-making. It operates in two modes: Problem Analysis (for root cause identification using IS/IS-NOT contrast) and Decision Analysis (for prioritizing options by screening MUSTs, weighting WANTs, and assessing adverse consequences). Ideal for complex engineering and business scenarios requiring structured evidence and risk assessment.

This framework applies the Lindy Effect principle to assess the expected remaining life of non-perishable technologies, ideas, or practices. It treats the current survival age as a strong prior for future longevity, guiding users to favor proven, long-surviving options. It is crucial when making critical, high-stakes choices (like selecting frameworks or protocols) where relevance must last years, requiring checks for domain drift and a clear burden of proof before adopting novelty.

A systematic methodology for resolving discrepancies between conceptual models (documentation, tests, diagrams, metrics) and actual observed behavior (live code execution or real data). This process mandates that observed reality (the 'territory') always overrules the theoretical map, ensuring system integrity and accurate knowledge updates.

This methodology provides a comprehensive framework for estimating buffered numbers—such as capacity limits, timeframes, or budgets—when making commitments under uncertainty. It guides users to calculate a buffer based on both residual estimation error and the potential cost of failure (breach cost), ensuring resilience against costly underestimation in critical systems or plans.

A systematic methodology for solving complex, multi-domain, or high-stakes problems where a single mental model creates blind spots. This process guides users to select 2-3 complementary models, assign distinct roles, define a conflict rule, and synthesize findings into a single, decision-ready recommendation.

This tool acts as a meta-skill guide, helping users systematically determine the most appropriate cognitive framework when faced with complex problem-solving tasks. It maps the problem's domain and type (e.g., diagnosis, strategy, architecture) to select the optimal primary thinking skill, preventing guesswork or arbitrary stacking of tools. It ensures the chosen method is justified by mechanism fit and relevance.

A rapid decision-making framework (Observe, Orient, Decide, Act) designed for high-pressure, dynamic environments. It advocates acting on high-probability signals (e.g., 70% confidence) immediately and cycling through observation and action quickly, rather than waiting for perfect certainty. Ideal for incident response, debugging moving targets, and time-bound crisis management.