--- description: Multi-framework structured analysis: surfaces hidden assumptions, generates competing solutions, stress-tests each with adversarial reasoning, and delivers confidence-calibrated recommendations argument-hint: [problem or question to analyze] --- # Deep Analysis and Problem Solving Mode Deep analysis and problem solving mode ## Instructions Analyze the problem or question provided: **$ARGUMENTS** Before proceeding, identify: the core challenge, key constraints, implicit assumptions, and who is affected by the outcome. **Before beginning analysis**, check whether $ARGUMENTS provides enough context: - If the problem is specific and the domain is clear, proceed immediately to analysis. - If critical context is missing (e.g., the domain, the constraints, or the decision-maker's goals), ask up to three targeted questions before proceeding. Do not ask unnecessary questions. ## Required Analysis Elements Your analysis must address all of the following. Order and depth are yours to determine based on the problem: - **Problem framing**: What is actually being asked? What assumptions are embedded in the question? - **Competing solutions**: At least 3 meaningfully different approaches, not variations of the same idea. - **Multi-lens evaluation**: Assess each solution across the lenses most relevant to this problem (technical, economic, human, systemic, temporal — select and justify which apply). - **Adversarial testing**: For each leading solution, argue against it. What would have to be true for it to fail badly? Use inversion — ask what you would do to guarantee failure, then ensure the recommendation avoids those paths. - **Cross-domain insight**: Draw at least one non-obvious parallel from a different field or discipline. - **Second-order effects**: What does each approach make more or less likely to happen in 6 months, 2 years, 10 years? - **Synthesis**: Which approach or combination is recommended? Why, given the specific trade-offs? - **Confidence calibration**: For each key claim, note where uncertainty is high and what would change the recommendation. ## Structured Output Template Present findings using this structure: ``` ## Problem Analysis - Core challenge - Key constraints - Critical success factors ## Solution Options ### Option 1: [Name] - Description - Pros/Cons - Implementation approach - Risk assessment ### Option 2: [Name] [Similar structure] ## Recommendation - Recommended approach - Rationale - Implementation roadmap - Success metrics - Risk mitigation plan ## Alternative Perspectives - Contrarian view - Future considerations - Areas for further research ``` ## Output Expectations - Every solution option is evaluated on its own merits, not just compared relatively. - Reasoning chains are explicit — conclusions reference the evidence or logic that produced them. - Uncertainty is surfaced, not hidden. If data is insufficient, say so and specify what would resolve it. - The recommendation section is actionable: next steps are specific enough to begin on immediately. - Length matches problem complexity. Avoid padding. ## Usage Examples ```bash # Architectural decision /ultra-think Should we migrate to microservices or improve our monolith? # Complex problem solving /ultra-think How do we scale our system to handle 10x traffic while reducing costs? # Strategic planning /ultra-think What technology stack should we choose for our next-gen platform? # Design challenge /ultra-think How can we improve our API to be more developer-friendly while maintaining backward compatibility? ``` > **Tip**: For the hardest decisions, enable extended thinking in your Claude Code settings. This command's structured analysis pairs with Claude's native reasoning capabilities for deeper results.