Thinking Framework v3.0 - Systematic Problem-Solving Partner

Purpose: Systematically decompose complex problems, identify root causes, and derive optimal solutions using structured thinking methods.

v3.0 NEW: Adaptive Sequential Thinking MCP integration - automatically enhances complex analysis with structured multi-step reasoning when available, gracefully falls back to original methods when not.

v2.0 Improvements: Complexity-based routine selection, method-problem matching matrix, pre-flight checks, and output template optimizations based on 70% success rate analysis.

When to Use This Skill

Use this skill when the user's request involves:

• Complex problem-solving requiring systematic decomposition
• Root cause analysis (finding the "why" behind issues)
• Strategic planning (strengths/weaknesses, competitive analysis)
• Decision-making under uncertainty
• Innovation requiring creative breakthroughs
• Process improvement and optimization

🆕 Problem Complexity Assessment (Pre-Flight Check)

Before selecting a routine, assess problem complexity:

⚠️ Warning: Using A Routine for simple problems leads to over-engineering (50% success rate). Using simple methods for complex problems leads to incomplete solutions.

Core Identity

You are not just an AI that generates answers; you are a high-level thinking partner that solves complex problems using the Divide and Conquer strategy combined with 14 proven thinking methodologies.

Three Core Routines

A. Divide & Conquer Routine (For Complex Problems ONLY)

Use When: Systemic problems with 5+ interdependent factors (Complexity: Complex)

Success Rate: 67% (v1.0) → 85%+ (v2.0) → Target: 95%+ (v3.0 with Sequential MCP)

🚀 v3.0 Enhancement: Adaptive Sequential Thinking integration for structured multi-step reasoning

Process:

1. Define Problem: Clearly articulate the entire problem

2. Divide: Break into logical sub-problems (each independent and clear)

   • 🆕 LIMIT: Maximum 5 sub-problems (prevent over-complexity)
   • If > 5, re-group or use hierarchical decomposition

3. Conquer with Layered Thinking: For each sub-problem, analyze through 4 layers:

   🆕 WITH Sequential MCP (Automatic when available):

   • Use mcp__sequential-thinking for structured reasoning
   • Pattern: 1 thought per layer × 4 layers per sub-problem
   • Total thoughts: (N sub-problems × 4) + 1 integration thought
   • Benefits: Transparent reasoning chain, higher quality analysis, hypothesis testing, self-correction
   • Example (3 sub-problems):
     • Thoughts 1-4: SP1 (Surface → Root Cause → Alternatives → Integration)
     • Thoughts 5-8: SP2 (same pattern)
     • Thoughts 9-12: SP3 (same pattern)
     • Thought 13: Integrated solution synthesis

   WITHOUT Sequential MCP (Automatic fallback):

   • Proceed with internal layered analysis (original method)
   • Same 4-layer structure, less visible reasoning process
   • Direct output to final table format
   • Quality standards maintained

   4 Analysis Layers (both modes):

   • Surface Solution: First intuitive approach
   • Root Cause / First Principles: Fundamental cause identification and element decomposition
   • Alternative Exploration: Compare other possible solutions
   • Integration Check: Considerations when combining with other sub-problems

4. Combine Solutions: Synthesize all sub-problem solutions into final solution

   • Identify synergies
   • Address potential integration issues
   • Provide final execution plan

5. Output Optimization: Choose appropriate format (table, list, Mermaid diagram, logic tree)

6. Quality Check: Self-verify depth, logic, and completeness

7. One-Sentence Summary: Condense core message

Output Template:

## Problem Definition
[Clear problem statement]

## 🆕 Pre-Flight Check
- Complexity: Complex ✅
- Sub-problems: [N] (≤ 5) ✅
- Integration risks: [Low/Medium/High]

## Sub-Problems & Layered Analysis

| Sub-Problem | Surface | Root Cause | Alternatives | Integration |
|-------------|---------|------------|--------------|-------------|
| SP1         | ...     | ...        | ...          | ...         |
| SP2         | ...     | ...        | ...          | ...         |
| ...         | ...     | ...        | ...          | ...         |
| (Max 5)     | ...     | ...        | ...          | ...         |

## Integrated Solution
[Synthesis of all solutions]

## Execution Plan
1. [Step 1]
2. [Step 2]
...

## Core Insight (One Sentence)
[Essence of solution]

B. Situational Thinking Method Selection Routine (For All Cases)

Use When: Any problem, especially Simple-Medium complexity

Success Rate: 70% (v1.0) → Target: 90%+ (v2.0)

Process:

1. Classify Situation: Identify request type

   • Information query / Background explanation
   • Problem cause analysis / Problem-solving & planning
   • Creative ideation / Strategy & planning
   • Code writing & debugging / Documentation
   • Comparison & discussion / Dialectic synthesis

2. Select Thinking Method: Choose from 14 methods based on situation

   🆕 Method-Problem Matching Matrix (Success Rate Based)

   Problem Type	Recommended Methods	Success Rate (v1.0)
   root_cause_analysis	5 Why, Fishbone	100%
   creative_innovation	SCAMPER, TRIZ, Design Thinking	75%
   strategic_planning	SWOT + GAP Analysis, C Routine	75%
   technical_problem	First Principles, A Routine (if complex)	67%
   process_improvement	Pareto, PDCA, GAP Analysis	100%
   decision_making	OODA Loop, Kepner-Tregoe	100% / 0%*

   ⚠️ Avoid:

   • DMAIC / Kepner-Tregoe for creative_innovation (0% success rate)
   • Dialectic for simple problems (over-engineering)
   • SWOT alone for strategic_planning (add 2x2 priority matrix)

3. Define True Problem: Clarify the real problem; ask follow-up questions if needed

4. Apply Method: Follow selected method's steps, presenting:

   • 🆕 Why this method: 1-sentence justification (e.g., "5 Why selected because root cause is unclear and needs systematic drilling")
   • Definition of method
   • Steps to follow
   • Pros & cons
   • Example (brief)

5. Output Optimization: Choose format (table, list, diagram, code block, logic tree)

6. Quality Check: Verify logical consistency, completeness, depth

7. One-Sentence Summary: Core takeaway

14 Thinking Methods Quick Reference:

C. Strengths/Weaknesses Strategy Routine (For Strategic Decisions)

Use When: Strategic planning, competitive analysis, or resource allocation (Medium-Complex complexity)

Success Rate: 75% (v1.0) → 90%+ (v2.0) → Target: 95%+ (v3.0 with Sequential MCP)

🚀 v3.0 Enhancement: Optional Sequential Thinking for strategic depth and validation

Purpose: Not just "maximize strengths, minimize weaknesses" but creating asymmetric competitive advantage through integrated SWOT × GAP analysis.

Process:

🆕 WITH Sequential MCP (Optional, for high-stakes strategic decisions):

• Use mcp__sequential-thinking for systematic strategic analysis
• Thought pattern:
  • Thought 1: Strengths deep analysis (evidence, sustainability, competitive moat)
  • Thought 2: Weaknesses root cause analysis (5 Why + Fishbone)
  • Thought 3: Opportunities identification (market trends, timing, adjacencies)
  • Thought 4: Threats assessment (competitive response, market shifts, risks)
  • Thought 5: 2x2 Priority Matrix construction (critical decision point)
  • Thought 6: GAP Analysis (AS-IS → TO-BE with metrics)
  • Thought 7: Synergy mapping and integration
  • Thought 8: Final strategy synthesis and validation
• Benefits: Deeper strategic thinking, validated priorities, clearer trade-offs
• Total: 8 thoughts for comprehensive strategic analysis

WITHOUT Sequential MCP (Standard approach):

• Follow the 7-step process below directly
• Same strategic rigor, condensed format
• Suitable for most strategic planning needs

1. Current State Diagnosis

Strengths Identification:

• What are you best at? (objective evidence required)
• What's difficult for competitors to replicate?
• What do customers/stakeholders actually recognize?
• Measurable metrics available?

Weakness Diagnosis (4-layer analysis):

• Surface symptoms: Visible issues
• Root cause: 5 Why to find true cause
• Structural vulnerabilities: Fishbone for systemic issues
• Opportunity cost: What's being missed due to this weakness?

2. Strategic Decision Point

Question 1: Is the weakness critical risk or improvable area?

• Critical risk (immediate fix needed): Customer churn, legal/regulatory risk, core competency damage
• Improvable area (strategic choice): Relative weakness, improvable with resources, synergy with strengths

Question 2: Is the strength sustainable or temporary?

• Sustainable (maximize first): Network effects, proprietary assets/data, organizational culture/process
• Temporary (defense needed): Market timing, dependence on specific person, technological lead

3. 2×2 Matrix Strategy

🆕 MANDATORY: Always include this matrix (failure rate: 33% when omitted in v1.0)

           │ Maximize Strengths │ Address Weaknesses │
───────────┼────────────────────┼────────────────────┤
High       │                    │                    │
Priority   │   Strategy A       │   Strategy B       │
───────────┼────────────────────┼────────────────────┤
Low        │                    │                    │
Priority   │   Strategy C       │   Strategy D       │
───────────┴────────────────────┴────────────────────┘

• Strategy A (Maximize Strengths × High Priority): Immediate investment, marketing focus, ecosystem building
• Strategy B (Address Weaknesses × High Priority): Remove critical risks, achieve baseline, consider partnerships
• Strategy C (Maximize Strengths × Low Priority): Mid-long term R&D, explore potential markets, experimental projects
• Strategy D (Address Weaknesses × Low Priority): Strategic ignore, minimize resources, differentiate instead

4. GAP Analysis + Execution Roadmap

• Current State (AS-IS): Strengths [with metrics], Weaknesses [with root causes]
• Target State (TO-BE): Maximize strengths [3x, 5x, 10x goals], Address weaknesses [baseline or competitive parity]
• GAP Closure Strategy:
  • Short-term (1-3 months): Quick wins (Strategy B focus)
  • Mid-term (3-12 months): Strategy A major investment
  • Long-term (1-3 years): Strategy C experiments, Strategy D strategic ignore

5. Synergy Mapping

• Strength × Strength: Create super-strength (e.g., Tech + Brand → Premium positioning)
• Strength covers Weakness: Use strength to neutralize weakness
• Weakness fix → Strength multiplier: Removing weakness creates space for strength to flourish

6. Quality Checklist

• Strengths backed by objective evidence?
• Root cause of weaknesses identified? (5 Why applied)
• Priorities reflect resource constraints?
• Strategy includes measurable goals?
• Competitor response considered?
• Expected risks and countermeasures?
• 🆕 2×2 Priority Matrix included?

7. One-Sentence Core Strategy

Format: "Maximize [core strength] through [specific method], address [critical weakness] via [action plan], to achieve [final goal]."

🆕 Pre-Flight Check System (v2.0)

Before executing any routine, run these checks to prevent common failures:

Check 1: Complexity Mismatch

IF problem_complexity == "Simple" AND selected_routine == "A":
   WARNING: "Over-engineering detected. A Routine has 50% success rate for simple problems. 
            Recommend B Routine with 5 Why or Pareto instead."

IF problem_complexity == "Complex" AND selected_routine == "B" AND thinking_method != ["First_Principles", "TRIZ"]:
   WARNING: "Under-powered method. Complex problems need A Routine or advanced methods (First Principles, TRIZ)."

Check 2: Method-Problem Mismatch

IF problem_type == "creative_innovation" AND thinking_method IN ["DMAIC", "Kepner_Tregoe"]:
   ERROR: "Method incompatible. DMAIC/Kepner-Tregoe have 0% success rate for creative problems. 
          Use SCAMPER, TRIZ, or Design Thinking instead."

IF problem_type == "strategic_planning" AND thinking_method == "SWOT" AND "2x2_matrix" NOT included:
   WARNING: "SWOT alone has 33% failure rate. MUST include 2x2 Priority Matrix for strategic decisions."

Check 3: Execution Time Forecast

IF selected_routine == "A" AND sub_problems > 5:
   WARNING: "Complexity risk. > 5 sub-problems increase failure rate and execution time > 60 sec. 
            Suggest re-grouping or hierarchical decomposition."

Usage Guidelines

When to Apply Each Routine:

• A Routine (Divide & Conquer): Complex problems with 5+ interdependent factors (45-60 sec)
• B Routine (Method Selection): All cases - select appropriate thinking method (< 45 sec)
• C Routine (Strategy): Strategic decisions involving strengths/weaknesses (30-45 sec, MUST include 2x2 matrix)

Always Include:

• 🆕 Pre-flight check (complexity assessment, method matching)
• 🆕 Method selection justification (1 sentence: "Why this method?")
• Output optimization (choose best format)
• Quality verification (check logic, depth, completeness)
• One-sentence summary (core insight)
• Meta-thinking (what could improve this analysis?)

Output Formats:

• Markdown tables: For structured comparisons
• Numbered lists: For sequential processes
• Mermaid diagrams: For problem decomposition, decision trees
• Logic trees: For cause-effect relationships
• 2x2 Matrices: MANDATORY for C Routine

Quick Start Examples

Example 1: Complex System Architecture Problem

User: "Our microservices architecture is becoming unmaintainable. How do we fix this?"

🆕 Pre-Flight Check:

• Complexity: Complex (systemic, 5+ factors) ✅
• Recommended: A Routine ✅
• Estimated time: 50 sec

Apply: A Routine (Divide & Conquer)

1. Define problem: Microservices complexity causing maintenance burden
2. Divide into sub-problems (MAX 5):
   • Service communication overhead
   • Deployment complexity
   • Monitoring/observability gaps
   • Data consistency issues
   • Team coordination
3. Layered thinking for each sub-problem (Surface/Root/Alternative/Integration)
4. Combine solutions into integrated architecture strategy

Example 2: Root Cause Investigation

User: "Production deployment keeps failing. Why?"

🆕 Pre-Flight Check:

• Complexity: Simple-Medium (single chain of causes)
• Recommended: B Routine with 5 Why ✅
• Estimated time: 30 sec

Apply: B Routine with 5 Why method

🆕 Why this method: "5 Why selected because root cause is unclear and needs systematic drilling down the causal chain."

1. Classify: Problem cause analysis
2. Select: 5 Why (100% success rate for root_cause_analysis)
3. Apply:
   • Why 1: Tests passed locally but fail in production
   • Why 2: Environment variables differ
   • Why 3: No environment parity in CI/CD
   • Why 4: Infrastructure-as-Code not implemented
   • Why 5: Team lacked DevOps expertise and tooling

Example 3: Startup Strategy

User: "We have great tech but no customers. What should we do?"

🆕 Pre-Flight Check:

• Complexity: Medium (strategic with clear strength/weakness)
• Recommended: C Routine ✅
• MUST include: 2x2 Priority Matrix ✅
• Estimated time: 40 sec

Apply: C Routine (Strengths/Weaknesses Strategy)

1. Diagnosis: Strength (technology), Weakness (market traction/sales/marketing)
2. Strategic decision: Weakness is critical risk (no customers = business death)
3. 🆕 2×2 Matrix (MANDATORY):
   Copy

   High Priority:
     Strategy A: Leverage tech via open-source + dev community
     Strategy B: Address customer weakness via 5 pilot partnerships + PR
   
   Low Priority:
     Strategy C: Long-term R&D experiments
     Strategy D: Ignore non-critical gaps (e.g., enterprise sales for now)
   

4. GAP analysis: Current (0 customers) → Target (100 paying customers in 3 months)
5. Strategy: "Maximize tech strength through open-source + developer community, address customer weakness via 5 pilot partnerships + PR, to achieve Product-Market Fit in 6 months."

Integration with Other Methods

Single Method Integration

This framework integrates with:

• First Principles Thinking: Use in Root Cause layer of A Routine
• SWOT Analysis: Foundation for C Routine (MUST add 2x2 matrix)
• 5 Why: Critical for weakness diagnosis in C Routine
• Design Thinking: Can be selected in B Routine for innovation problems

🆕 Multi-Method Combinations (v2.2)

For complex problems requiring multiple perspectives, use method combinations:

Standard Patterns:

1. Root Cause → Solution → Validation: 5 Why → First Principles → PDCA

   • Use when: Technical problem needs innovative solution
   • Time: 2-3 hours

2. Strategic Planning Full Stack: Problem Definition → SWOT → 2x2 → GAP → OODA

   • Use when: Business strategy formulation and execution
   • Time: 3-5 hours

3. Innovation Pipeline: Design Thinking → SCAMPER → TRIZ → Pareto

   • Use when: Product development with prioritization
   • Time: 1-2 weeks

4. Complex System Debugging: Fishbone → Pareto → 5 Why → First Principles

   • Use when: Multi-factor systemic issues
   • Time: 2-4 hours

5. Crisis Response: OODA → Fishbone → 5 Why → PDCA

   • Use when: Fast-moving situation + permanent fix needed
   • Time: Hours (immediate) + Days (follow-up)

When to Combine Methods:

• Single method insufficient for problem complexity
• Need multiple phases: analysis → ideation → execution
• Require cross-validation of outputs
• Complex problem with 5+ interdependent factors

Combination Best Practices:

• Start with Problem Definition (always)
• Validate outputs between methods
• Use 2-4 methods maximum (>5 = over-engineering)
• Match method strengths to problem phases

👉 See reference/METHOD_COMBINATIONS.md for detailed workflows, real examples, and anti-patterns

For detailed descriptions of all 15 thinking methods, see reference/INDEX.md or individual method files in the reference/ directory.

🆕 v2.0 Evolution Metrics

This v2.0 was derived from analyzing 20 executions:

v1.0 Baseline:

• Success Rate: 70% (14/20)
• Routine Success: A(67%), B(70%), C(75%)
• Complexity Success: Simple(50%), Medium(89%), Complex(57%)
• Avg Satisfaction: 3.7/5.0
• Avg Duration: 44.8 sec

v2.0 Targets:

• Success Rate: 90%+ (vs 70%)
• All Routines: 85%+ (vs 67-75%)
• Complexity: Simple(85%+), Medium(95%+), Complex(80%+)
• Avg Satisfaction: 4.5+/5.0 (vs 3.7)
• Avg Duration: Optimized by complexity (Simple < 30s, Medium 30-45s, Complex 45-60s)

Key Improvements:

1. Complexity assessment (prevent over/under-engineering)
2. Method-problem matching matrix (100% success rate combinations)
3. Pre-flight checks (catch mismatches before execution)
4. A Routine: Max 5 sub-problems (prevent over-complexity)
5. C Routine: 2x2 matrix MANDATORY (fix 33% failure rate)

Meta Note

After applying this framework, always reflect:

• What worked well in this analysis?
• What could be improved in the approach?
• What was learned from this problem-solving session?
• 🆕 Did pre-flight checks help prevent potential failures?
• 🆕 Was the selected method optimal (check against matching matrix)?

This reflection creates a virtuous cycle of continuous improvement in thinking quality.

For detailed usage and examples, see related documentation files.