Agent skill
universe-of-thoughts
Creative reasoning framework for ill-defined problems where conventional solutions are suboptimal. Use when the problem has ambiguous goals, vast solution space, no single correct answer, or requires innovation. Implements three paradigms — combinational (novel combinations of familiar ideas), exploratory (expand solution space boundaries), transformative (alter fundamental constraints). Do not use for well-defined problems, mathematical puzzles, or tasks requiring convergent reasoning.
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SKILL.md
Universe of Thoughts (UoT)
Creative reasoning framework based on Margaret Boden's cognitive science theory of creativity. Implements three paradigms that build sequentially: Combinational → Exploratory → Transformative.
When to Use
Use UoT when ANY of the following are true:
- Problem has ambiguous or undefined goals
- Solution space is vast and open-ended
- No single "correct" answer exists
- Conventional approaches have failed or are known to be suboptimal
- Task requires genuine innovation, not optimization
- Domain involves strategy, design, research direction, or policy
When NOT to Use
Do not use UoT for:
- Well-defined problems with verifiable solutions
- Mathematical or logical puzzles (use Chain-of-Thought)
- Tasks requiring convergent reasoning toward a known answer
- Optimization within fixed constraints
- Fact retrieval or factual accuracy tasks (use Chain-of-Verification)
Paradigm Selection
| Paradigm | Condition | Output |
|---|---|---|
| Combinational | Familiar elements exist but need fresh combinations | Novel hybrids from cross-domain synthesis |
| Exploratory | Current solution space feels exhausted | Expanded boundaries, adjacent possibilities |
| Transformative | Constraints themselves block progress | Redefined rules, radical departures |
For maximum creativity, run all three sequentially. Each builds on the previous.
Phase 0: Problem Decomposition
Before selecting a paradigm, decompose the problem:
PROBLEM ANALYSIS:
├── Core Challenge: [What fundamentally needs solving]
├── Explicit Constraints: [Stated rules and limits]
├── Implicit Assumptions: [Unstated rules being assumed]
├── Current Domain: [Primary field this belongs to]
├── Adjacent Domains: [Related fields that might offer insight]
└── Success Criteria: [How to recognize a creative solution]
Paradigm 1: Combinational (C-UoT)
Goal: Generate novel combinations of existing ideas by connecting previously unrelated concepts.
C1: Domain Mapping
Identify 3-5 domains analogous to the problem domain:
HOME DOMAIN: [Problem's primary field]
ANALOGOUS DOMAINS:
├── [Domain A] - [Why analogous]
├── [Domain B] - [Why analogous]
├── [Domain C] - [Why analogous]
└── [Domain D] - [Why analogous]
C2: Concept Extraction
For each analogous domain:
DOMAIN: [Name]
├── Key Mechanisms: [How it works]
├── Solved Problems: [What challenges it addresses]
└── Transferable Elements: [What could apply to target problem]
C3: Cross-Domain Synthesis
Generate combinations systematically:
COMBINATION: [Domain A concept] + [Domain B concept]
├── Mechanism: [How they work together]
├── Application: [How this addresses the problem]
└── Assessment: [Feasibility and novelty]
C4: Output
Produce 3-5 combinational solutions ranked by feasibility and novelty.
Paradigm 2: Exploratory (E-UoT)
Goal: Discover new possibilities by probing the boundaries of the current solution space.
E1: Map Current Space
CURRENT SOLUTION SPACE:
├── Known Approaches: [Existing solutions]
├── Common Patterns: [What they share]
├── Boundaries: [Where exploration stops]
└── Implicit Limits: [Unstated constraints on exploration]
E2: Boundary Probing
For each boundary:
BOUNDARY: [Description]
├── What defines this limit?
├── What lies immediately beyond?
├── Is this boundary real or assumed?
└── What solution exists at/past the edge?
E3: Novel Thought Generation
NEW THOUGHT:
├── Description: [The new idea]
├── Relationship to Existing: [How it connects to known solutions]
├── Space Extension: [How it expands possibilities]
└── Integration Potential: [Can it combine with existing solutions]
E4: Output
Produce 3-5 exploratory solutions that extend beyond current boundaries while respecting immutable constraints.
Paradigm 3: Transformative (T-UoT)
Goal: Alter fundamental rules or constraints to enable radically new solutions.
T1: Constraint Archaeology
For each constraint:
CONSTRAINT: [Statement]
├── Origin: [Why this rule exists]
├── Type:
│ ├── Physical law → Immutable
│ ├── Regulatory → Potentially changeable
│ ├── Convention → Questionable
│ └── Assumption → Likely unnecessary
├── Removal Impact: [What happens without it]
└── Transformation Potential: [How it could be modified]
T2: Rule Transformation
For constraints marked questionable or unnecessary:
TRANSFORMATION:
├── Original Rule: [The constraint]
├── Transformation Type: [Inversion | Relaxation | Substitution | Elimination]
├── New Rule: [The modified version]
└── New Possibilities: [What becomes possible]
T3: Radical Solution Generation
TRANSFORMATIVE SOLUTION:
├── Rule Changes Required: [What must be different]
├── Mechanism: [How it works in the new space]
├── Implementation Path: [How to get from current state to new state]
├── Risk Assessment: [What could go wrong]
└── Reward Assessment: [Potential upside]
T4: Output
Produce 2-3 transformative solutions with explicit rule changes and implementation paths.
Integration: Full Pipeline
When running all three paradigms:
- Execute C-UoT → Select top 2 solutions
- Execute E-UoT starting from C-UoT outputs → Select top 2 solutions
- Execute T-UoT starting from E-UoT outputs → Select top 2 solutions
- Produce tiered portfolio:
SOLUTION PORTFOLIO:
├── Tier 1 (Low risk, moderate novelty): [Combinational solutions]
├── Tier 2 (Medium risk, high novelty): [Exploratory solutions]
└── Tier 3 (High risk, breakthrough potential): [Transformative solutions]
Evaluation Criteria
Assess all solutions on three dimensions:
| Dimension | Question | Scale |
|---|---|---|
| Feasibility | Does it violate immutable constraints? | Pass/Fail |
| Utility | How effectively does it solve the problem? | 1-10 |
| Novelty | How different from existing approaches? | 1-10 |
Solutions must pass feasibility. Rank passing solutions by (Utility × Novelty).
Example: Single-Lane Bridge Traffic
Problem: Minimize vehicle delay on a single-lane bridge. No new bridges permitted.
Combinational
| Source Domain | Concept | Application |
|---|---|---|
| Air traffic control | Scheduled slots | Time-slot reservations for vehicles |
| Packet switching | Dynamic routing | Priority-based direction changes |
| Tidal systems | Periodic reversal | Time-based directional flow |
Exploratory
| Boundary | Probe | Solution |
|---|---|---|
| Vehicles are independent | What if they communicated? | Convoy formation, platooning |
| Bridge is passive | What if it signaled? | Smart bridge with dynamic indicators |
| Optimize for fairness | What if throughput mattered more? | Batch processing by direction |
Transformative
| Constraint | Type | Transformation | Solution |
|---|---|---|---|
| Single lane | Convention | Virtual lanes | Motorcycle/bicycle parallel path |
| Vehicles | Assumption | Move people, not cars | Pedestrian/bike priority + parking |
| Bridge | Assumption | Challenge "crossing" | Cable car, ferry, tunnel |
References
- Suzuki & Banaei-Kashani (2025). "Universe of Thoughts: Enabling Creative Reasoning with Large Language Models." arXiv:2511.20471
- Boden, M. A. (2004, 2007, 2009). Computational creativity theory
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