Ultra-Think: Deep Structured Analysis
Surfaces hidden assumptions, generates competing solutions and stress-tests each before recommending one.
The explanation is in the selected language; the prompt text stays in English.
Why use it
You face a hard decision and a single confident answer feels untrustworthy. The assistant builds at least three different solutions and stress-tests each with counterarguments.
How to use it
Replace [YOUR INPUT] with the problem, your constraints and your goal. If context is thin, it asks up to three questions first. The more specific your answers, the more useful the analysis.
Short example
Problem: keep a small online course on Telegram or move it to its own site. Constraints: tight budget, five hours a week, 300 subscribers.
What to expect
Problem framing, three solutions, adversarial testing of each, effects at six months and two years, a recommendation and confidence notes per claim.
Precautions and tips
- Treat the recommendation as input for thinking, not a final verdict.
- It does not replace a professional for financial, legal or medical decisions.
- Verify any numbers and sources yourself.
# Deep Analysis and Problem Solving Mode
Deep analysis and problem solving mode
## Instructions
Analyze the problem or question provided: **[YOUR INPUT]**
Before proceeding, identify: the core challenge, key constraints, implicit assumptions, and who is affected by the outcome.
**Before beginning analysis**, check whether [YOUR INPUT] 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.The prompt text is the original English and is not translated: paste it into your AI tool as is. Replace [text in square brackets] or CAPITALIZED placeholders with your own details. Always check the answer.
Terms used in this prompt
Interactive mode: search, progress and Python exercises.
