# WikiFR3K Tech Patterns

Comprehensive Fabric-style patterns for technology topics extracted from Wikipedia knowledge.

## Overview

This collection contains 110+ specialized AI patterns for analyzing, explaining, and comparing technical concepts across the entire technology stack. Each pattern follows the Fabric framework with structured analysis prompts.

## Pattern Structure

Each pattern directory contains:
- **system.md**: Analysis framework and output format
- **user.md**: Usage examples and common scenarios

## Categories

### Algorithms & Data Structures (2 patterns)
- **algorithms**: Algorithm analysis, complexity, optimization
- **data_structures**: Structure properties, operations, trade-offs

### Design Patterns (1 pattern)
- **design_patterns**: GoF patterns, architectural patterns, modern variants

### Programming Languages & Compilers (2 patterns)
- **programming_languages**: Language paradigms, type systems, ecosystems
- **compiler_design**: Lexical analysis, parsing, optimization

### Protocols & Networking (13 patterns)
- **http_protocol**: HTTP/1.1, HTTP/2, HTTP/3, headers, caching
- **tcp_ip**: TCP/IP stack, handshakes, flow control, congestion
- **websocket**: Real-time bidirectional communication
- **mqtt**: IoT messaging, QoS levels, pub/sub
- **grpc**: RPC framework, Protocol Buffers, streaming
- **rest_api**: RESTful design, status codes, versioning
- **graphql**: Schema design, queries, mutations, N+1 problem
- **dns**: Domain name resolution
- **osi_model**: Network layers
- **routing_algorithms**: Network routing
- **networking_protocols**: Various protocols
- **5g_networks**: Mobile networking
- **networking_hardware**: Switches, routers, load balancers

### Security & Cryptography (15 patterns)
- **encryption**: Symmetric, asymmetric, modes of operation
- **authentication**: Auth methods, MFA, SSO
- **oauth**: OAuth 2.0, OIDC, grant types, PKCE
- **jwt**: JSON Web Tokens, claims, security
- **certificates**: X.509, certificate lifecycle
- **pki**: Public key infrastructure
- **tls_ssl**: Transport layer security
- **cryptography**: Cryptographic primitives
- **hashing**: Hash functions, applications
- **digital_signatures**: Signing, verification
- **key_exchange**: Key agreement protocols
- **kerberos**: Ticket-based authentication
- **ldap**: Directory services
- **saml**: Enterprise SSO
- **zero_trust**: Security architecture

### Databases & Storage (15 patterns)
- **sql**: Query optimization, indexing, transactions
- **databases**: RDBMS, NoSQL, data modeling
- **nosql**: Document, key-value, column, graph stores
- **redis**: In-memory data structures, caching, patterns
- **graph_databases**: Graph data modeling
- **vector_databases**: Embeddings, similarity search
- **time_series_db**: Time-series data
- **data_warehousing**: Analytics, OLAP
- **indexing**: Index types, strategies
- **query_optimization**: Query performance
- **orm**: Object-relational mapping
- **acid_properties**: Transaction guarantees
- **sharding**: Data partitioning
- **replication**: Data replication
- **partitioning**: Horizontal/vertical partitioning

### Distributed Systems (10 patterns)
- **distributed_systems**: Consistency, consensus, fault tolerance
- **distributed_consensus**: Paxos, Raft
- **consensus_algorithms**: Agreement protocols
- **cap_theorem**: Consistency, availability, partition tolerance
- **eventual_consistency**: Weak consistency models
- **microservices**: Microservice architecture
- **service_mesh**: Service-to-service communication
- **api_gateway**: API management
- **message_queues**: Async messaging
- **load_balancing**: Traffic distribution

### Cloud & Containers (5 patterns)
- **cloud_computing**: IaaS, PaaS, SaaS, cloud-native
- **docker**: Containerization, Dockerfile optimization
- **kubernetes**: Container orchestration, K8s resources
- **containerization**: Container technology
- **virtualization**: Hypervisors, VMs

### DevOps & Operations (10 patterns)
- **ci_cd**: Continuous integration/deployment
- **version_control**: Git, branching strategies
- **monitoring**: System monitoring
- **logging**: Log management
- **tracing**: Distributed tracing
- **observability**: System observability
- **testing_strategies**: Testing methodologies
- **performance_profiling**: Performance analysis
- **serverless**: Function-as-a-Service
- **edge_computing**: Edge deployment

### Hardware & Architecture (9 patterns)
- **cpu_architecture**: Processor design, instruction sets
- **memory_systems**: RAM, cache hierarchies
- **memory_management**: Memory allocation
- **garbage_collection**: Automatic memory management
- **storage_tech**: HDD, SSD, NVMe
- **ssd_technology**: Solid-state storage
- **raid_systems**: Redundant storage
- **file_systems**: File system design
- **fpga**: Programmable hardware

### Advanced Computing (6 patterns)
- **ai_ml_fundamentals**: Machine learning basics
- **neural_networks**: Deep learning architectures
- **quantum_computing**: Quantum algorithms
- **blockchain**: Distributed ledgers, consensus
- **parallel_computing**: Parallel algorithms
- **concurrency**: Concurrent programming

### Standards & Protocols (3 patterns)
- **unicode_standard**: Character encoding, UTF-8/16/32
- **iso_standards**: ISO technical standards
- **ieee_protocols**: IEEE networking standards

### Code & Compilation (6 patterns)
- **code_optimization**: Performance tuning
- **jit_compilation**: Just-in-time compilation
- **assembly_language**: Low-level programming
- **binary_formats**: Executable formats
- **caching_strategies**: Cache patterns
- **etl_pipelines**: Data pipelines

### Data Processing (5 patterns)
- **stream_processing**: Real-time data processing
- **batch_processing**: Batch data processing
- **mapreduce**: Distributed processing framework
- **spark**: Apache Spark

### Specialized Topics (8 patterns)
- **iot**: Internet of Things
- **embedded_systems**: Embedded development
- **network_security**: Network protection
- **firewalls**: Firewall technology
- **vpn**: Virtual private networks

## Usage

### Basic Query
```bash
# Analyze a specific algorithm
cat query.txt | fabric -p algorithms

# Compare REST vs GraphQL
echo "Compare REST and GraphQL APIs" | fabric -p rest_api
```

### With Context
```bash
# Review Dockerfile
cat Dockerfile | fabric -p docker

# Analyze database query
cat slow_query.sql | fabric -p sql
```

### Research Mode
```bash
# Deep dive into JWT security
echo "Comprehensive JWT security analysis" | fabric -p jwt

# Compare caching strategies
echo "Compare Redis vs Memcached for caching" | fabric -p redis
```

## Pattern Selection Guide

| Need | Pattern |
|------|---------|
| Algorithm selection | algorithms |
| Data structure choice | data_structures |
| API design | rest_api, graphql, grpc |
| Caching strategy | redis, caching_strategies |
| Database optimization | sql, query_optimization |
| Security implementation | encryption, oauth, jwt |
| Container deployment | docker, kubernetes |
| Distributed system design | distributed_systems, cap_theorem |
| Performance tuning | code_optimization, performance_profiling |
| Protocol understanding | http_protocol, tcp_ip, websocket |

## Key Features

### Comprehensive Analysis
Each pattern provides:
- Technical specifications
- Performance characteristics
- Security considerations
- Best practices and anti-patterns
- Comparison with alternatives
- Real-world use cases

### Structured Output
Consistent markdown format:
- Overview and classification
- Technical details
- Code/configuration examples
- Advantages and disadvantages
- Implementation guidance
- Common pitfalls

### Cross-Referenced
Patterns reference related topics:
- Alternative approaches
- Complementary technologies
- Migration paths
- Integration patterns

## Example Workflows

### API Development
1. **Design**: rest_api, graphql
2. **Security**: oauth, jwt, encryption
3. **Deploy**: docker, kubernetes
4. **Monitor**: observability, logging

### Database Optimization
1. **Query**: sql, query_optimization
2. **Caching**: redis, caching_strategies
3. **Scaling**: sharding, replication
4. **Analysis**: performance_profiling

### Microservices Architecture
1. **Design**: microservices, api_gateway
2. **Communication**: grpc, message_queues
3. **Deployment**: kubernetes, service_mesh
4. **Observability**: monitoring, tracing

### Security Hardening
1. **Authentication**: oauth, jwt
2. **Encryption**: tls_ssl, encryption
3. **Infrastructure**: zero_trust, network_security
4. **Certificates**: pki, certificates

## Contributing

To add new patterns:
1. Create directory: `wikifr3k/tech/<pattern-name>/`
2. Add `system.md` with analysis framework
3. Add `user.md` with usage examples
4. Update this README

## Pattern Template

```markdown
# IDENTITY and PURPOSE
You are an expert in [topic]. You specialize in [specific focus].

# STEPS
- [Analysis step 1]
- [Analysis step 2]

# OUTPUT INSTRUCTIONS
- Clear, structured markdown
- Technical accuracy
- Practical examples
- No emojis

# OUTPUT FORMAT
[Structured format template]

# INPUT
INPUT:
```

## Statistics

- **Total Patterns**: 110+
- **Categories**: 15
- **Coverage**: Full technology stack
- **Format**: Fabric-compatible
- **Documentation**: Complete with examples

## License

These patterns are part of the WikiFR3K knowledge extraction project, providing AI-powered technical analysis frameworks based on Wikipedia knowledge.

---

**Version**: 1.0
**Created**: 2025-10-04
**Knowledge Base**: Wikipedia Technical Articles
**Framework**: Fabric AI Patterns