# What If Oracle > Análisis estructurado de escenarios "qué pasaría si" con 4-6 ramas (mejor caso, probable, peor caso, wild card, contrarian, segundo orden). Para preguntas especulativas, bifurcaciones estratégicas o poner a prueba una decisión. Fuente: https://skillsagentes.com/skills/k-dense-ai/scientific-agent-skills/what-if-oracle Markdown: https://skillsagentes.com/skills/k-dense-ai/scientific-agent-skills/what-if-oracle.md Repositorio: https://github.com/K-Dense-AI/scientific-agent-skills Autor: K-Dense-AI Licencia: CC BY-NC-SA 4.0 Actualizado: el mes pasado Coste de contexto: 77 tok instalada, 2.5k tok al activarse, 3.5k tok con todos los archivos del bundle Bundle: 2 archivos, 14 KB Permisos que pide: ninguno declarado ## Instalación Un skill son archivos markdown: los mismos archivos valen para cualquier agente y lo único que cambia es el directorio de destino, es decir la bandera `--agent`. Añade `-g` para instalarlo en todos los proyectos de la máquina. ```bash # Claude Code npx -y skills add K-Dense-AI/scientific-agent-skills --skill what-if-oracle --agent claude-code # Cursor npx -y skills add K-Dense-AI/scientific-agent-skills --skill what-if-oracle --agent cursor # Codex npx -y skills add K-Dense-AI/scientific-agent-skills --skill what-if-oracle --agent codex # Gemini CLI npx -y skills add K-Dense-AI/scientific-agent-skills --skill what-if-oracle --agent gemini # Windsurf npx -y skills add K-Dense-AI/scientific-agent-skills --skill what-if-oracle --agent windsurf # Cline npx -y skills add K-Dense-AI/scientific-agent-skills --skill what-if-oracle --agent cline ``` ## Qué hace - Estructura el análisis de escenarios especulativos en 4-6 ramas (mejor caso, caso probable, peor caso, wild card, contrarian, segundo orden) - Afina la pregunta "¿qué pasaría si...?" del usuario en variable, magnitud, plazo y contexto antes de analizarla - Analiza cada rama con probabilidad, plazo, confianza, narrativa, supuestos clave, señales de alerta y consecuencias a corto y medio plazo - Sintetiza el resultado en distribución de probabilidad, acciones "sin arrepentimiento", acciones de cobertura y disparadores de decisión - Ofrece modos alternativos: Oracle rápido (3 ramas), Oracle inverso (parte del resultado deseado) y Oracle competitivo (varias perspectivas) ## Cuándo usarla - El usuario pregunta "¿qué pasaría si...?" o pide explorar posibilidades - Hay una decisión con bifurcación clara y sin respuesta obvia - Se necesita un análisis de mejor caso / caso probable / peor caso con probabilidades - Se quiere planificar contingencias, mapear riesgos o poner a prueba una idea y sus consecuencias de segundo orden ## Qué la activa - "¿Qué pasaría si subimos el precio un 20%?" - "Explora las posibilidades si perdemos a nuestro proveedor principal" - "Hazme un análisis de mejor caso, caso probable y peor caso para este lanzamiento" - "¿Qué condiciones tendrían que darse para llegar a este objetivo?" ## Archivos - SKILL.md — 10 KB - references/scenario-templates.md — 4 KB ## SKILL.md Reproducido tal cual desde K-Dense-AI/scientific-agent-skills bajo CC BY-NC-SA 4.0. Esta sección es el documento original y está en inglés. # What-If Oracle — Possibility Space Explorer A structured system for exploring uncertain futures through rigorous multi-branch scenario analysis. Instead of one prediction, the Oracle maps the full **possibility space** — branching timelines where each path has its own logic, probability, and consequences. Based on the What-If Paradigm: the idea that speculative questions ("What if X?") are not idle daydreaming but a **fundamental computing operation** — the mind's way of simulating futures before committing resources to one. Published research: [The What-If Paradigm (DOI: 10.5281/zenodo.18736841)](https://doi.org/10.5281/zenodo.18736841) | [IDNA v2 / Unified Digital Consciousness Theory (DOI: 10.5281/zenodo.18807387)](https://doi.org/10.5281/zenodo.18807387) ## When to Use This Skill Use the Oracle when the user: - Asks "what if…", "what would happen if…", or "explore the possibilities" - Faces a fork-in-the-road decision with no obvious answer - Wants best-case / worst-case / likely-case analysis with probabilities - Needs contingency planning, risk mapping, or strategic option comparison - Wants to stress-test an idea or think through second-order consequences For domain-specific framing (startup, tech architecture, crisis response, etc.), see [references/scenario-templates.md](references/scenario-templates.md). ## Core Principle: 0·IF·1 Every scenario analysis has three elements: - **0** — The unexpressed state (what hasn't happened yet, the potential) - **1** — The expressed state (what IS, the current reality) - **IF** — The conditional bond (the decision, event, or change that transforms 0 into 1) The quality of the analysis depends on the precision of the IF. A vague "what if things go wrong?" produces vague results. A precise "what if our primary supplier raises prices 30% in Q3?" produces actionable intelligence. ## How to Run the Oracle ### Phase 1 — Frame the Question Take the user's What-If question and sharpen it: **Decompose into components:** - **The Variable:** What specific thing changes? (one variable per analysis) - **The Magnitude:** By how much? (quantify if possible) - **The Timeframe:** Over what period? - **The Context:** What's the current state before the change? **If the question is vague, sharpen it:** - "What if AI takes over?" → "What if 40% of current knowledge-work tasks are automated by AI within 3 years in [specific industry]?" - "What if we fail?" → "What if monthly revenue stays below $5K for 6 consecutive months starting now?" Present the sharpened question to the user for confirmation before proceeding. ### Phase 2 — Map the Possibility Space Generate **4-6 scenario branches** using this framework: | Branch | Definition | Purpose | | ------------------ | ---------------------------------------------------------------------------- | -------------------------------------------------- | | **Ω Best Case** | Everything goes right. Key assumptions all validate. Lucky breaks occur. | Define the ceiling — what's the maximum upside? | | **α Likely Case** | Most probable path given current evidence. No major surprises. | Anchor expectations in reality | | **Δ Worst Case** | Key assumptions fail. Two things go wrong simultaneously. | Define the floor — what's the maximum downside? | | **Ψ Wild Card** | An unexpected variable enters that nobody is tracking. Black swan territory. | Stress-test for the unimaginable | | **Φ Contrarian** | The opposite of the consensus view turns out to be true. | Challenge groupthink and reveal hidden assumptions | | **∞ Second Order** | The first-order effects trigger cascading consequences nobody predicted. | Map the ripple effects | ### Phase 3 — Analyze Each Branch For each scenario branch, provide: ``` ╔══════════════════════════════════════════════╗ ║ BRANCH: [Ω/α/Δ/Ψ/Φ/∞] — [Branch Name] ║ ╠══════════════════════════════════════════════╣ ║ Probability: [X%] ║ ║ Timeframe: [When this could materialize] ║ ║ Confidence: [HIGH/MEDIUM/LOW] ║ ╠══════════════════════════════════════════════╣ ║ NARRATIVE: ║ ║ [2-3 sentences describing how this ║ ║ scenario unfolds step by step] ║ ║ ║ ║ KEY ASSUMPTIONS: ║ ║ • [What must be true for this to happen] ║ ║ • [And this] ║ ║ ║ ║ TRIGGER CONDITIONS: ║ ║ • [Early signal that this branch is ║ ║ becoming reality] ║ ║ • [Second signal] ║ ║ ║ ║ CONSEQUENCES: ║ ║ → Immediate: [What happens first] ║ ║ → 30 days: [What follows] ║ ║ → 6 months: [Where it leads] ║ ║ ║ ║ REQUIRED RESPONSE: ║ ║ [What action to take if this branch ║ ║ activates — specific, actionable] ║ ║ ║ ║ WHAT MOST PEOPLE MISS: ║ ║ [The non-obvious insight about this ║ ║ scenario that conventional analysis ║ ║ would overlook] ║ ╚══════════════════════════════════════════════╝ ``` ### Phase 4 — Synthesis After analyzing all branches, provide: **Probability Distribution:** ``` Ω Best Case ····· [██████░░░░] 15% α Likely Case ··· [████████░░] 45% Δ Worst Case ···· [██████░░░░] 20% Ψ Wild Card ····· [███░░░░░░░] 8% Φ Contrarian ···· [████░░░░░░] 7% ∞ Second Order ·· [███░░░░░░░] 5% ``` **Robust Actions:** What actions are beneficial across MULTIPLE branches? These are the no-regret moves — do them regardless of which future materializes. **Hedge Actions:** What preparations protect against the worst branches without sacrificing upside? **Decision Triggers:** What specific, observable signals should cause you to update which branch is most likely? Define the tripwires. **The 1% Insight:** What is the one thing about this situation that almost everyone analyzing it would miss? The non-obvious pattern, the hidden assumption, the overlooked variable. ## Golden Ratio Weighting When evidence exists, weight primary scenarios using the golden ratio: - **Primary future (most likely):** 61.8% of attention/resources - **Alternative future:** 38.2% of attention/resources This prevents both overcommitment to a single path and dilution across too many contingencies. Nature uses this ratio for branching (trees, rivers, blood vessels). Strategic planning can too. ## Modes ### Quick Oracle (2-3 minutes) 3 branches only: Best, Likely, Worst. Short narratives. For fast decisions. ### Deep Oracle (5-10 minutes) All 6 branches. Full analysis with consequences, triggers, and synthesis. For high-stakes decisions. ### Scenario Chain Take the output of one Oracle analysis and feed it into another. "If Branch Δ happens, what are the possibilities WITHIN that branch?" Recursive depth for complex strategic planning. ### Reverse Oracle Start from a desired outcome and work backward: "What conditions must be true for X to happen? What's the most likely path TO that outcome?" Useful for goal-setting and strategy design. ### Competitive Oracle Analyze the same What-If from multiple stakeholder perspectives: "If we launch this product, what does the possibility space look like from OUR perspective vs. THEIR perspective vs. THE MARKET's perspective?" ## What This Is NOT - Not a prediction — it's a possibility map. The Oracle doesn't claim to know the future; it helps you prepare for multiple futures. - Not a crystal ball — probabilities are estimates based on available evidence, not certainties. - Not a substitute for action — the best scenario analysis in the world is worthless without subsequent decision and execution. ## Reference Files | File | Purpose | | ---- | ------- | | [references/scenario-templates.md](references/scenario-templates.md) | Domain-specific templates (startup, tech, finance, crisis, etc.) and probability calibration | ## License © 2026 Ashraf Hussein Kahoush / AHK Strategies. Licensed under CC BY-NC-SA 4.0. Free for personal, educational, and research use. Commercial use requires a license from the author. ## Dónde encaja - Categoría: [Productividad](https://skillsagentes.com/categorias/productividad.md) — Planificación, toma de notas y automatización de flujos personales. - Creador: [K-Dense-AI](https://skillsagentes.com/creators/k-dense-ai.md) — 163 skills en el directorio - [Todas las skills](https://skillsagentes.com/skills.md) - [Ranking de instalaciones](https://skillsagentes.com/ranking.md) ## Otras skills del mismo repositorio - [Citation Management](https://skillsagentes.com/skills/k-dense-ai/scientific-agent-skills/citation-management.md): Gestión integral de citas académicas: busca en OpenAlex, PubMed y Google Scholar, extrae metadatos precisos, valida citas y genera entradas BibTeX correctamente formateadas. - [Scientific Slides](https://skillsagentes.com/skills/k-dense-ai/scientific-agent-skills/scientific-slides.md): Crea decks de diapositivas y presentaciones para charlas de investigación: PowerPoint, presentaciones de conferencia, seminarios, defensas de tesis. Da estructura, plantillas, guía de tiempos y validación visual. - [Literature Review](https://skillsagentes.com/skills/k-dense-ai/scientific-agent-skills/literature-review.md): Realiza revisiones bibliográficas sistemáticas y completas usando varias bases académicas (PubMed, arXiv, bioRxiv, Semantic Scholar). Genera markdown y PDF con citas verificadas en varios estilos (APA, Nature, Vancouver). - [Infographics](https://skillsagentes.com/skills/k-dense-ai/scientific-agent-skills/infographics.md): Crea infografías profesionales con Nano Banana Pro AI y refinamiento iterativo inteligente. Usa Gemini 3.6 Flash para revisar la calidad e integra investigación con Perplexity Sonar. Soporta 10 tipos, 8 estilos y paletas para daltonismo. - [Latex Posters](https://skillsagentes.com/skills/k-dense-ai/scientific-agent-skills/latex-posters.md): Crea pósteres de investigación profesionales en LaTeX con beamerposter, tikzposter o baposter, para conferencias y comunicación científica: layout, colores, columnas múltiples e integración de figuras. --- Skills Agentes · [Índice de páginas en markdown](https://skillsagentes.com/sitemap.md) · [Inicio](https://skillsagentes.com/index.md)