MCP HubMCP Hub
Retour aux compétences

what-if-oracle

K-Dense-AI
Mis à jour Today
26,534
2,743
26,534
Voir sur GitHub
Testsaitesting

À propos

La compétence "oracle des hypothèses" permet une analyse de scénarios structurée en générant 4 à 6 branches de possibilités distinctes (comme les cas optimaux, pessimistes et anticonformistes) pour des questions spéculatives. Les développeurs doivent l'utiliser lorsque les utilisateurs ont besoin d'explorer des futurs incertains, de tester la résistance de décisions ou de planifier des embranchements stratégiques. Elle cartographie systématiquement la logique, la probabilité et les conséquences de chaque voie potentielle au lieu de fournir une prédiction unique.

Installation rapide

Claude Code

Recommandé
Principal
npx skills add K-Dense-AI/claude-scientific-skills -a claude-code
Commande PluginAlternatif
/plugin add https://github.com/K-Dense-AI/claude-scientific-skills
Git CloneAlternatif
git clone https://github.com/K-Dense-AI/claude-scientific-skills.git ~/.claude/skills/what-if-oracle

Copiez et collez cette commande dans Claude Code pour installer cette compétence

Documentation

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) | IDNA v2 / Unified Digital Consciousness Theory (DOI: 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.

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:

BranchDefinitionPurpose
Ω Best CaseEverything goes right. Key assumptions all validate. Lucky breaks occur.Define the ceiling — what's the maximum upside?
α Likely CaseMost probable path given current evidence. No major surprises.Anchor expectations in reality
Δ Worst CaseKey assumptions fail. Two things go wrong simultaneously.Define the floor — what's the maximum downside?
Ψ Wild CardAn unexpected variable enters that nobody is tracking. Black swan territory.Stress-test for the unimaginable
Φ ContrarianThe opposite of the consensus view turns out to be true.Challenge groupthink and reveal hidden assumptions
∞ Second OrderThe 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

FilePurpose
references/scenario-templates.mdDomain-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.

Dépôt GitHub

K-Dense-AI/claude-scientific-skills
Chemin: skills/what-if-oracle
0
agent-skillsai-scientistbioinformaticschemoinformaticsclaudeclaude-skills

Compétences associées

evaluating-llms-harness

Tests

Cette compétence Claude exécute le lm-evaluation-harness pour évaluer les modèles de langage sur plus de 60 tâches académiques standardisées telles que MMLU et GSM8K. Elle est conçue pour permettre aux développeurs de comparer la qualité des modèles, de suivre les progrès de l'entraînement ou de rapporter des résultats académiques. L'outil prend en charge différents backends, incluant les modèles HuggingFace et vLLM.

Voir la compétence

cloudflare-cron-triggers

Tests

Cette compétence fournit une connaissance complète pour la mise en œuvre de Déclencheurs Cron Cloudflare afin de planifier des Workers à l'aide d'expressions cron. Elle couvre la configuration de tâches périodiques, de travaux de maintenance et de flux de travail automatisés, tout en traitant des problèmes courants tels que les expressions cron non valides et les problèmes de fuseau horaire. Les développeurs peuvent l'utiliser pour configurer des gestionnaires planifiés, tester des déclencheurs cron et intégrer avec Workflows et Green Compute.

Voir la compétence

webapp-testing

Tests

Cette Compétence Claude fournit une boîte à outils basée sur Playwright pour tester des applications web locales via des scripts Python. Elle permet la vérification frontend, le débogage d'interface utilisateur, la capture d'écrans et la consultation des journaux, tout en gérant les cycles de vie du serveur. Utilisez-la pour les tâches d'automatisation de navigateur, mais exécutez les scripts directement plutôt que de lire leur code source pour éviter la pollution du contexte.

Voir la compétence

finishing-a-development-branch

Tests

Cette compétence aide les développeurs à finaliser leur travail en vérifiant que les tests passent, puis en présentant des options d'intégration structurées. Elle guide le processus de fusion, de création de PRs ou de nettoyage des branches une fois l'implémentation terminée. Utilisez-la lorsque votre code est prêt et testé pour finaliser systématiquement le cycle de développement.

Voir la compétence