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:

  1. Execute C-UoT → Select top 2 solutions
  2. Execute E-UoT starting from C-UoT outputs → Select top 2 solutions
  3. Execute T-UoT starting from E-UoT outputs → Select top 2 solutions
  4. 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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