gh-dotclaude-marketplace-plugins-adaptive-learning/commands/pattern_discovery.md

model, allowed-tools, argument-hint, description

model	allowed-tools	argument-hint	description
claude-opus-4-1	Task, Read, Write, Grep, Bash(*), Glob	<data-domain> [--pattern-type=<category>] [--abstraction-level=<depth>] [--transfer-scope=<application-breadth>]	Deep structural pattern recognition with cross-domain transfer identification

Pattern Discovery Engine

Identify deep structural patterns across domains, recognize recurring frameworks, and facilitate pattern transfer for enhanced problem-solving and understanding. Transform seemingly unrelated information into coherent pattern libraries that reveal universal principles and enable innovative applications.

Pattern Category Framework

Structural Patterns (Organizational and architectural patterns)

[Extended thinking: Identify how components organize, relate, and create stable arrangements across different contexts and domains.]

Architectural Organization:

• Hierarchical Structures: Tree-like organizations with clear parent-child relationships
• Network Topologies: Interconnected nodes with distributed relationships and flows
• Layered Architectures: Stratified systems with abstraction levels and interfaces
• Modular Systems: Component-based organizations with defined boundaries and interactions
• Fractal Patterns: Self-similar structures that repeat at different scales

Relationship Patterns:

• Dependency Chains: Sequential relationships where elements depend on predecessors
• Feedback Loops: Circular relationships where outputs influence inputs
• Hub-and-Spoke: Central nodes that coordinate distributed peripheral elements
• Mesh Networks: Distributed connectivity with multiple pathways and redundancy
• Pipeline Flows: Sequential processing stages with defined inputs and outputs

Stability Mechanisms:

• Balance Points: Equilibrium states that systems naturally seek
• Tension Resolution: How opposing forces create stable dynamic states
• Adaptation Protocols: Mechanisms that maintain structure while enabling change
• Boundary Maintenance: How systems preserve identity while interacting with environment
• Recovery Patterns: How systems restore stability after disruption

Behavioral Patterns (Process and interaction patterns)

[Extended thinking: Recognize recurring sequences of actions, interactions, and transformations that create predictable outcomes.]

Process Sequences:

• Initiation-Development-Resolution: Three-phase patterns common across many domains
• Preparation-Action-Reflection: Learning and improvement cycles
• Sensing-Processing-Responding: Information handling and decision-making patterns
• Gathering-Organizing-Applying: Knowledge management and utilization cycles
• Planning-Executing-Evaluating: Project and goal achievement patterns

Interaction Dynamics:

• Negotiation Patterns: How different entities reach agreements or resolve conflicts
• Coordination Mechanisms: How multiple agents synchronize actions and share information
• Competition Dynamics: How entities compete for resources while maintaining system stability
• Cooperation Strategies: How entities collaborate for mutual benefit and shared goals
• Communication Protocols: How information transfers between system components

Change Patterns:

• Gradual Evolution: Incremental change patterns that preserve continuity
• Punctuated Equilibrium: Stable periods interrupted by rapid transformation phases
• Cyclical Variations: Repeating patterns of change over time
• Threshold Effects: Sudden changes when accumulated factors reach critical points
• Adaptation Spirals: Iterative improvement cycles that create progressive development

Causal Patterns (Cause-effect relationship patterns)

[Extended thinking: Identify recurring causal mechanisms that explain how events, actions, or conditions produce specific outcomes.]

Direct Causation:

• Linear Cause-Effect: Straightforward relationships where specific causes produce predictable effects
• Proportional Response: Effects that scale directly with cause intensity
• Threshold Activation: Causes that must reach minimum levels before producing effects
• Saturation Limits: Points where additional causes produce diminishing effects
• Cascade Triggers: Single causes that initiate sequences of secondary effects

Complex Causation:

• Multiple Contributing Factors: Outcomes that require combination of several causes
• Synergistic Effects: Causes that produce greater effects when combined than when separate
• Inhibiting Factors: Elements that prevent or reduce causal effects
• Context Dependencies: Causal relationships that vary with environmental conditions
• Emergent Causation: Effects that arise from system properties rather than individual components

Temporal Causation:

• Delayed Effects: Causes separated from effects by significant time intervals
• Cumulative Impact: Effects that build gradually through repeated causal exposure
• Timing Sensitivity: Causal effectiveness that depends on when causes are applied
• Sequential Dependencies: Causal chains where later effects depend on earlier ones
• Cyclical Causation: Repeating causal patterns over time cycles

Evolutionary Patterns (Change and adaptation patterns)

[Extended thinking: Recognize how systems develop, adapt, and evolve over time through various mechanisms and pressures.]

Development Stages:

• Emergence: How new patterns and systems initially form
• Growth: Expansion and development phases with characteristic dynamics
• Maturity: Stable operation periods with established patterns and capabilities
• Decline: Degradation phases with characteristic failure modes
• Transformation: Metamorphosis into fundamentally different forms

Adaptation Mechanisms:

• Selection Pressures: Environmental factors that favor certain characteristics
• Variation Generation: Mechanisms that create diversity and new possibilities
• Inheritance Patterns: How successful adaptations transfer to new generations
• Mutation Events: Random changes that sometimes produce beneficial innovations
• Co-Evolution: How interdependent systems adapt together over time

Innovation Patterns:

• Incremental Improvement: Gradual enhancement of existing approaches
• Disruptive Change: Innovations that fundamentally alter system dynamics
• Convergent Solutions: Independent development of similar solutions to common problems
• Cross-Pollination: Innovation through combination of ideas from different domains
• Paradigm Shifts: Fundamental changes in underlying assumptions and approaches

Optimization Patterns (Efficiency and improvement patterns)

[Extended thinking: Identify recurring approaches to maximizing performance, minimizing waste, and achieving optimal outcomes.]

Resource Optimization:

• Pareto Distributions: 80/20 patterns where small inputs produce large outputs
• Bottleneck Management: Focus on constraining factors that limit overall system performance
• Load Balancing: Distribution of work or resources to maximize efficiency
• Just-in-Time: Minimizing waste through precise timing and minimal inventory
• Economies of Scale: Efficiency gains from increased size or volume

Performance Patterns:

• Trade-off Optimization: Balancing competing objectives for optimal overall performance
• Diminishing Returns: Points where additional investment produces smaller benefits
• Sweet Spots: Optimal operating ranges where efficiency is maximized
• Feedback Control: Self-regulating systems that maintain optimal performance
• Continuous Improvement: Incremental optimization through systematic enhancement

Quality Enhancement:

• Error Prevention: Patterns that reduce mistakes and improve reliability
• Redundancy Design: Backup systems and alternatives that ensure robustness
• Simplification: Reduction of complexity while maintaining functionality
• Standardization: Common approaches that improve consistency and efficiency
• Measurement-Driven: Improvement through systematic observation and data analysis

Abstraction Level Framework

Concrete Level (Specific implementation patterns)

[Extended thinking: Identify patterns in specific, tangible implementations with clear, observable characteristics.]

Implementation Focus:

• Specific Technologies: Patterns within particular tools, platforms, or technologies
• Concrete Examples: Real-world instances with specific details and context
• Measurable Outcomes: Patterns with quantifiable results and clear success metrics
• Direct Observation: Patterns visible through immediate experience and data
• Practical Application: Patterns that directly inform specific actions and decisions

Pattern Recognition Process:

1. Instance Collection: Gather multiple examples of similar implementations
2. Common Element Identification: Find shared characteristics across instances
3. Variation Analysis: Understand how patterns adapt to different contexts
4. Success Factor Isolation: Identify which elements contribute to effectiveness
5. Application Guidelines: Develop specific rules for pattern implementation

Conceptual Level (Abstract principle patterns)

[Extended thinking: Extract essential principles that transcend specific implementations while maintaining practical relevance.]

Abstraction Process:

• Principle Extraction: Identify fundamental rules underlying concrete patterns
• Generalization: Extend patterns beyond original contexts to broader applications
• Essential Elements: Distill patterns to core components necessary for effectiveness
• Variable Identification: Recognize which aspects can change while preserving pattern integrity
• Context Independence: Develop understanding that applies across different situations

Pattern Categories:

• Design Principles: Fundamental rules for creating effective solutions
• Behavioral Guidelines: Core principles for successful interactions and processes
• System Properties: Essential characteristics that determine system effectiveness
• Success Factors: Key elements that predict favorable outcomes
• Universal Rules: Principles that apply across many different domains and contexts

Meta Level (Pattern-of-patterns recognition)

[Extended thinking: Recognize higher-order patterns about how patterns themselves form, evolve, and relate to each other.]

Meta-Pattern Categories:

• Pattern Formation: How patterns emerge and establish themselves
• Pattern Evolution: How patterns change and develop over time
• Pattern Interaction: How different patterns combine and influence each other
• Pattern Transfer: How patterns move between domains and contexts
• Pattern Hierarchies: How patterns organize at different levels of abstraction

Meta-Analysis Framework:

1. Pattern Catalog Development: Build comprehensive library of identified patterns
2. Relationship Mapping: Identify connections and dependencies between patterns
3. Evolution Tracking: Monitor how patterns change and develop
4. Transfer Mechanisms: Understand how patterns successfully move between domains
5. Emergence Recognition: Identify how new patterns arise from pattern combinations

Universal Level (Cross-domain applicable patterns)

[Extended thinking: Identify patterns so fundamental they appear across completely different domains, representing universal principles of organization and function.]

Universal Pattern Types:

• Information Patterns: How information organizes, flows, and transforms across all domains
• Energy Patterns: How energy converts, transfers, and dissipates in all systems
• Growth Patterns: Universal principles of development and expansion
• Balance Patterns: Fundamental stability and equilibrium mechanisms
• Adaptation Patterns: Universal principles of change and response to environment

Cross-Domain Recognition:

• Mathematical Structures: Patterns describable by universal mathematical principles
• Physical Laws: Patterns reflecting fundamental physical properties and constraints
• Logical Relationships: Patterns based on universal logical and reasoning principles
• Information Theory: Patterns relating to universal principles of communication and computation
• Complexity Science: Patterns from universal principles of complex system behavior

Transfer Facilitation Framework

Cross-Domain Pattern Application

[Extended thinking: Enable successful application of patterns from one domain to enhance understanding and problem-solving in different domains.]

Transfer Methodology:

1. Source Pattern Analysis: Deeply understand pattern in its original context
2. Target Domain Assessment: Evaluate characteristics of application domain
3. Compatibility Evaluation: Determine which pattern aspects transfer effectively
4. Adaptation Strategy: Modify pattern elements for new domain requirements
5. Implementation Validation: Test pattern effectiveness in new context

Transfer Types:

• Direct Transfer: Patterns that apply with minimal modification
• Analogical Transfer: Patterns that require metaphorical adaptation
• Structural Transfer: Patterns where underlying structure applies but surface features change
• Principle Transfer: Patterns where fundamental rules apply but implementation differs
• Creative Transfer: Patterns that inspire innovative approaches in new domains

Pattern Library Development

[Extended thinking: Build comprehensive, organized collection of patterns that supports pattern recognition, learning, and application.]

Library Organization:

• Category Classification: Organize patterns by type, domain, and application
• Abstraction Hierarchy: Structure patterns from specific to universal levels
• Relationship Networks: Map connections and dependencies between patterns
• Transfer Guides: Provide guidance for applying patterns across domains
• Evolution Tracking: Monitor pattern development and emerging variations

Library Components:

• Pattern Descriptions: Clear articulation of pattern characteristics and mechanisms
• Context Information: Conditions where patterns are effective and applicable
• Implementation Guides: Specific instructions for pattern application
• Example Collections: Multiple instances demonstrating pattern variations
• Success Metrics: Measures for evaluating pattern effectiveness

Execution Examples

Example 1: Software Architecture Pattern Discovery

pattern_discovery "microservices implementations across different companies" --pattern-type=structural --abstraction-level=conceptual --transfer-scope=cross-industry

Structural Pattern Recognition:

• Service Decomposition Patterns: Domain-driven boundaries, business capability alignment, data ownership principles
• Communication Patterns: API gateways, event-driven messaging, service mesh architectures
• Data Management Patterns: Database per service, event sourcing, CQRS separation
• Resilience Patterns: Circuit breakers, bulkheads, timeout configurations, graceful degradation
• Deployment Patterns: Container orchestration, infrastructure as code, continuous deployment

Conceptual Abstraction:

• Boundary Principle: Systems benefit from clear responsibility boundaries with well-defined interfaces
• Autonomy Principle: Components perform better when they can operate independently
• Resilience Principle: Distributed systems require explicit failure handling and recovery mechanisms
• Evolution Principle: Architectures must support independent component development and deployment
• Observability Principle: Complex systems require comprehensive monitoring and tracing

Cross-Industry Transfer Applications:

• Manufacturing: Apply service decomposition to production line organization
• Healthcare: Use resilience patterns for medical system reliability
• Education: Apply autonomy principles to curriculum module design
• Finance: Transfer observability patterns to risk monitoring systems

Example 2: Learning Process Pattern Discovery

pattern_discovery "successful skill acquisition across different domains" --pattern-type=behavioral --abstraction-level=universal --transfer-scope=educational

Behavioral Pattern Recognition:

• Deliberate Practice: Focused practice on specific weaknesses with immediate feedback
• Spaced Repetition: Distributed practice over time for long-term retention
• Progressive Complexity: Gradual increase in challenge level as competence builds
• Multi-Modal Engagement: Combination of different learning approaches for reinforcement
• Peer Interaction: Learning through teaching, collaboration, and community participation

Universal Pattern Abstraction:

• Feedback Loop Optimization: All learning systems benefit from rapid, specific feedback
• Cognitive Load Management: Human learning capacity requires careful challenge calibration
• Memory Consolidation: Time-based repetition strengthens long-term knowledge storage
• Transfer Facilitation: Abstract pattern recognition enables cross-domain application
• Motivation Sustainability: Intrinsic engagement maintains long-term learning effort

Educational Transfer Applications:

• Technical Training: Apply deliberate practice to programming skill development
• Language Learning: Use spaced repetition for vocabulary acquisition
• Medical Education: Apply multi-modal engagement to clinical skill development
• Creative Skills: Transfer peer interaction patterns to art and design education
• Professional Development: Apply progressive complexity to leadership skill building

Example 3: Innovation Process Pattern Discovery

pattern_discovery "breakthrough innovations in technology and science" --pattern-type=evolutionary --abstraction-level=meta --transfer-scope=organizational

Evolutionary Pattern Recognition:

• Paradigm Preparation: Extended periods of incremental progress that reveal paradigm limitations
• Catalyst Events: Specific triggers that enable paradigm-shifting innovations
• Resistance and Adoption: Predictable patterns of initial rejection followed by gradual acceptance
• Ecosystem Transformation: How breakthrough innovations reshape entire industries and practices
• Co-Evolution: How innovations drive complementary innovations in related areas

Meta-Pattern Abstraction:

• Innovation Pattern Lifecycle: How innovation patterns themselves evolve and mature
• Cross-Domain Innovation Transfer: How breakthrough approaches migrate between fields
• Innovation Culture Patterns: Organizational characteristics that facilitate breakthrough thinking
• Innovation Network Effects: How innovation success creates conditions for further innovation
• Innovation Timing Patterns: When breakthrough innovations are most likely to succeed

Organizational Transfer Applications:

• R&D Management: Apply paradigm preparation patterns to research planning
• Product Development: Use catalyst event patterns to identify innovation opportunities
• Change Management: Transfer resistance and adoption patterns to organizational transformation
• Strategic Planning: Apply ecosystem transformation patterns to market strategy
• Culture Development: Use innovation culture patterns to build creative organizations

Advanced Pattern Features

Pattern Evolution Tracking

[Extended thinking: Monitor how patterns change over time and predict future pattern development.]

Evolution Mechanisms:

• Environmental Pressure: How changing conditions force pattern adaptation
• Technological Enablement: How new capabilities enable pattern evolution
• Cross-Pollination: How patterns evolve through contact with other domains
• User Innovation: How pattern users modify and improve patterns
• Systematic Optimization: How deliberate improvement efforts evolve patterns

Pattern Synthesis

[Extended thinking: Combine multiple patterns to create new, more powerful hybrid patterns.]

Synthesis Methods:

• Pattern Combination: Merging compatible patterns for enhanced effectiveness
• Pattern Intersection: Finding common elements that create new pattern possibilities
• Pattern Contrast: Using pattern differences to generate innovative alternatives
• Pattern Hierarchy: Organizing patterns at different levels for comprehensive solutions
• Pattern Ecosystem: Creating networks of interrelated patterns for complex challenges

Success Indicators

Pattern Recognition Quality

• Pattern Validity: Identified patterns accurately represent underlying structures
• Pattern Completeness: Recognition captures essential pattern elements
• Pattern Generalizability: Patterns apply successfully across appropriate contexts
• Pattern Predictability: Patterns enable accurate prediction of outcomes
• Pattern Utility: Patterns provide valuable guidance for problem-solving and decision-making

Transfer Effectiveness

• Successful Application: Patterns work effectively when applied in new domains
• Innovation Generation: Pattern transfer leads to creative solutions and approaches
• Understanding Enhancement: Pattern recognition improves comprehension and insight
• Problem-Solving Acceleration: Patterns enable faster and more effective solution development
• Knowledge Integration: Patterns create connections between previously separate knowledge areas

The pattern_discovery command reveals universal principles and recurring structures that transcend specific contexts, creating powerful tools for understanding, prediction, and innovation through deep structural pattern recognition and cross-domain transfer.