Add modernized Payment Intents pattern with Payment Element

- Restore Payment Intents flow removed by PR, updated for modern best practices
- Use Payment Element instead of legacy Card Element
- Use stripe.confirmPayment() instead of deprecated confirmCardPayment()
- Use automatic_payment_methods instead of hardcoded payment_method_types
- Split Python/JS into separate fenced code blocks for clarity
- Add guidance on when to use Payment Intents vs Checkout Sessions
- Renumber subsequent patterns (Subscription → 4, Customer Portal → 5)

.claude-plugin/marketplace.json

@@ -6,8 +6,8 @@
     "url": "https://github.com/wshobson"
   },
   "metadata": {
-    "description": "Production-ready workflow orchestration with 72 focused plugins, 112 specialized agents, and 146 skills - optimized for granular installation and minimal token usage",
+    "description": "Production-ready workflow orchestration with 73 focused plugins, 112 specialized agents, and 146 skills - optimized for granular installation and minimal token usage",
-    "version": "1.5.4"
+    "version": "1.5.1"
   },
   "plugins": [
     {
@@ -114,6 +114,19 @@
       "license": "MIT",
       "category": "workflows"
     },
+    {
+      "name": "code-review-ai",
+      "source": "./plugins/code-review-ai",
+      "description": "AI-powered architectural review and code quality analysis",
+      "version": "1.2.0",
+      "author": {
+        "name": "Seth Hobson",
+        "email": "seth@major7apps.com"
+      },
+      "homepage": "https://github.com/wshobson/agents",
+      "license": "MIT",
+      "category": "quality"
+    },
     {
       "name": "code-refactoring",
       "source": "./plugins/code-refactoring",
@@ -168,8 +181,8 @@
     },
     {
       "name": "llm-application-dev",
-      "description": "LLM application development with LangGraph, RAG systems, vector search, and AI agent architectures for Claude 4.6 and GPT-5.2",
+      "description": "LLM application development with LangGraph, RAG systems, vector search, and AI agent architectures for Claude 4.5 and GPT-5.2",
-      "version": "2.0.4",
+      "version": "2.0.3",
       "author": {
         "name": "Seth Hobson",
         "email": "seth@major7apps.com"
@@ -183,7 +196,7 @@
       "name": "agent-orchestration",
       "source": "./plugins/agent-orchestration",
       "description": "Multi-agent system optimization, agent improvement workflows, and context management",
-      "version": "1.2.1",
+      "version": "1.2.0",
       "author": {
         "name": "Seth Hobson",
         "email": "seth@major7apps.com"
@@ -391,7 +404,7 @@
       "name": "performance-testing-review",
       "source": "./plugins/performance-testing-review",
       "description": "Performance analysis, test coverage review, and AI-powered code quality assessment",
-      "version": "1.2.1",
+      "version": "1.2.0",
       "author": {
         "name": "Seth Hobson",
         "email": "seth@major7apps.com"
@@ -897,7 +910,7 @@
     {
       "name": "conductor",
       "description": "Context-Driven Development plugin that transforms Claude Code into a project management tool with structured workflow: Context → Spec & Plan → Implement",
-      "version": "1.2.1",
+      "version": "1.2.0",
       "author": {
         "name": "Seth Hobson",
         "email": "seth@major7apps.com"

README.md

@@ -1,18 +1,18 @@
 # Claude Code Plugins: Orchestration and Automation
 
-> **⚡ Updated for Opus 4.6, Sonnet 4.6 & Haiku 4.5** — Three-tier model strategy for optimal performance
+> **⚡ Updated for Opus 4.5, Sonnet 4.5 & Haiku 4.5** — Three-tier model strategy for optimal performance
 
 [![Run in Smithery](https://smithery.ai/badge/skills/wshobson)](https://smithery.ai/skills?ns=wshobson&utm_source=github&utm_medium=badge)
 
 > **🎯 Agent Skills Enabled** — 146 specialized skills extend Claude's capabilities across plugins with progressive disclosure
 
-A comprehensive production-ready system combining **112 specialized AI agents**, **16 multi-agent workflow orchestrators**, **146 agent skills**, and **79 development tools** organized into **72 focused, single-purpose plugins** for [Claude Code](https://docs.claude.com/en/docs/claude-code/overview).
+A comprehensive production-ready system combining **112 specialized AI agents**, **16 multi-agent workflow orchestrators**, **146 agent skills**, and **79 development tools** organized into **73 focused, single-purpose plugins** for [Claude Code](https://docs.claude.com/en/docs/claude-code/overview).
 
 ## Overview
 
 This unified repository provides everything needed for intelligent automation and multi-agent orchestration across modern software development:
 
-- **72 Focused Plugins** - Granular, single-purpose plugins optimized for minimal token usage and composability
+- **73 Focused Plugins** - Granular, single-purpose plugins optimized for minimal token usage and composability
 - **112 Specialized Agents** - Domain experts with deep knowledge across architecture, languages, infrastructure, quality, data/AI, documentation, business operations, and SEO
 - **146 Agent Skills** - Modular knowledge packages with progressive disclosure for specialized expertise
 - **16 Workflow Orchestrators** - Multi-agent coordination systems for complex operations like full-stack development, security hardening, ML pipelines, and incident response
@@ -20,7 +20,7 @@ This unified repository provides everything needed for intelligent automation an
 
 ### Key Features
 
-- **Granular Plugin Architecture**: 72 focused plugins optimized for minimal token usage
+- **Granular Plugin Architecture**: 73 focused plugins optimized for minimal token usage
 - **Comprehensive Tooling**: 79 development tools including test generation, scaffolding, and security scanning
 - **100% Agent Coverage**: All plugins include specialized agents
 - **Agent Skills**: 146 specialized skills following for progressive disclosure and token efficiency
@@ -49,7 +49,7 @@ Add this marketplace to Claude Code:
 /plugin marketplace add wshobson/agents
 ```
 
-This makes all 72 plugins available for installation, but **does not load any agents or tools** into your context.
+This makes all 73 plugins available for installation, but **does not load any agents or tools** into your context.
 
 ### Step 2: Install Plugins
 
@@ -73,7 +73,7 @@ Install the plugins you need:
 
 # Security & quality
 /plugin install security-scanning           # SAST with security skill
-/plugin install comprehensive-review       # Multi-perspective code analysis
+/plugin install code-review-ai             # AI-powered code review
 
 # Full-stack orchestration
 /plugin install full-stack-orchestration   # Multi-agent workflows
@@ -114,7 +114,7 @@ rm -rf ~/.claude/plugins/cache/claude-code-workflows && rm ~/.claude/plugins/ins
 
 ### Core Guides
 
-- **[Plugin Reference](docs/plugins.md)** - Complete catalog of all 72 plugins
+- **[Plugin Reference](docs/plugins.md)** - Complete catalog of all 73 plugins
 - **[Agent Reference](docs/agents.md)** - All 112 agents organized by category
 - **[Agent Skills](docs/agent-skills.md)** - 146 specialized skills with progressive disclosure
 - **[Usage Guide](docs/usage.md)** - Commands, workflows, and best practices
@@ -203,14 +203,14 @@ Strategic model assignment for optimal performance and cost:
 
 | Tier       | Model    | Agents | Use Case                                                                                        |
 | ---------- | -------- | ------ | ----------------------------------------------------------------------------------------------- |
-| **Tier 1** | Opus 4.6 | 42     | Critical architecture, security, ALL code review, production coding (language pros, frameworks) |
+| **Tier 1** | Opus 4.5 | 42     | Critical architecture, security, ALL code review, production coding (language pros, frameworks) |
 | **Tier 2** | Inherit  | 42     | Complex tasks - user chooses model (AI/ML, backend, frontend/mobile, specialized)               |
 | **Tier 3** | Sonnet   | 51     | Support with intelligence (docs, testing, debugging, network, API docs, DX, legacy, payments)   |
 | **Tier 4** | Haiku    | 18     | Fast operational tasks (SEO, deployment, simple docs, sales, content, search)                   |
 
-**Why Opus 4.6 for Critical Agents?**
+**Why Opus 4.5 for Critical Agents?**
 
-- 80.8% on SWE-bench (industry-leading)
+- 80.9% on SWE-bench (industry-leading)
 - 65% fewer tokens for complex tasks
 - Best for architecture decisions and security audits
 
@@ -218,14 +218,14 @@ Strategic model assignment for optimal performance and cost:
 Agents marked `inherit` use your session's default model, letting you balance cost and capability:
 
 - Set via `claude --model opus` or `claude --model sonnet` when starting a session
-- Falls back to Sonnet 4.6 if no default specified
+- Falls back to Sonnet 4.5 if no default specified
 - Perfect for frontend/mobile developers who want cost control
 - AI/ML engineers can choose Opus for complex model work
 
 **Cost Considerations:**
 
-- **Opus 4.6**: $5/$25 per million input/output tokens - Premium for critical work
+- **Opus 4.5**: $5/$25 per million input/output tokens - Premium for critical work
-- **Sonnet 4.6**: $3/$15 per million tokens - Balanced performance/cost
+- **Sonnet 4.5**: $3/$15 per million tokens - Balanced performance/cost
 - **Haiku 4.5**: $1/$5 per million tokens - Fast, cost-effective operations
 - Opus's 65% token reduction on complex tasks often offsets higher rate
 - Use `inherit` tier to control costs for high-volume use cases
@@ -283,13 +283,13 @@ Uses kubernetes-architect agent with 4 specialized skills for production-grade c
 
 ## Plugin Categories
 
-**24 categories, 72 plugins:**
+**24 categories, 73 plugins:**
 
 - 🎨 **Development** (4) - debugging, backend, frontend, multi-platform
 - 📚 **Documentation** (3) - code docs, API specs, diagrams, C4 architecture
 - 🔄 **Workflows** (5) - git, full-stack, TDD, **Conductor** (context-driven development), **Agent Teams** (multi-agent orchestration)
 - ✅ **Testing** (2) - unit testing, TDD workflows
-- 🔍 **Quality** (2) - comprehensive review, performance
+- 🔍 **Quality** (3) - code review, comprehensive review, performance
 - 🤖 **AI & ML** (4) - LLM apps, agent orchestration, context, MLOps
 - 📊 **Data** (2) - data engineering, data validation
 - 🗄️ **Database** (2) - database design, migrations
@@ -330,7 +330,7 @@ Three-tier architecture for token efficiency:
 ```
 claude-agents/
 ├── .claude-plugin/
-│   └── marketplace.json          # 72 plugins
+│   └── marketplace.json          # 73 plugins
 ├── plugins/
 │   ├── python-development/
 │   │   ├── agents/               # 3 Python experts

docs/architecture.md

@@ -334,7 +334,7 @@ Feature Development Workflow:
 1. backend-development:feature-development
 2. security-scanning:security-hardening
 3. unit-testing:test-generate
-4. comprehensive-review:full-review
+4. code-review-ai:ai-review
 5. cicd-automation:workflow-automate
 6. observability-monitoring:monitor-setup
 ```

docs/plugins.md

@@ -1,6 +1,6 @@
 # Complete Plugin Reference
 
-Browse all **71 focused, single-purpose plugins** organized by category.
+Browse all **72 focused, single-purpose plugins** organized by category.
 
 ## Quick Start - Essential Plugins
 
@@ -68,6 +68,14 @@ Multi-agent coordination from backend → frontend → testing → security →
 
 Generate pytest (Python) and Jest (JavaScript) unit tests automatically with comprehensive edge case coverage.
 
+**code-review-ai** - AI-powered code review
+
+```bash
+/plugin install code-review-ai
+```
+
+Architectural analysis, security assessment, and code quality review with actionable feedback.
+
 ### Infrastructure & Operations
 
 **cloud-infrastructure** - Cloud architecture design
@@ -142,10 +150,11 @@ Next.js, React + Vite, and Node.js project setup with pnpm and TypeScript best p
 | **unit-testing**  | Automated unit test generation (Python/JavaScript) | `/plugin install unit-testing`  |
 | **tdd-workflows** | Test-driven development methodology                | `/plugin install tdd-workflows` |
 
-### 🔍 Quality (2 plugins)
+### 🔍 Quality (3 plugins)
 
 | Plugin                         | Description                                   | Install                                      |
 | ------------------------------ | --------------------------------------------- | -------------------------------------------- |
+| **code-review-ai**             | AI-powered architectural review               | `/plugin install code-review-ai`             |
 | **comprehensive-review**       | Multi-perspective code analysis               | `/plugin install comprehensive-review`       |
 | **performance-testing-review** | Performance analysis and test coverage review | `/plugin install performance-testing-review` |
 

docs/usage.md

@@ -70,6 +70,7 @@ Claude Code automatically selects and coordinates the appropriate agents based o
 
 | Command                             | Description                |
 | ----------------------------------- | -------------------------- |
+| `/code-review-ai:ai-review`         | AI-powered code review     |
 | `/comprehensive-review:full-review` | Multi-perspective analysis |
 | `/comprehensive-review:pr-enhance`  | Enhance pull requests      |
 
@@ -360,7 +361,7 @@ Compose multiple plugins for complex scenarios:
 /unit-testing:test-generate
 
 # 4. Review the implementation
-/comprehensive-review:full-review
+/code-review-ai:ai-review
 
 # 5. Set up CI/CD
 /cicd-automation:workflow-automate

plugins/agent-orchestration/.claude-plugin/plugin.json

@@ -1,6 +1,6 @@
 {
   "name": "agent-orchestration",
-  "version": "1.2.1",
+  "version": "1.2.0",
   "description": "Multi-agent system optimization, agent improvement workflows, and context management",
   "author": {
     "name": "Seth Hobson",

plugins/agent-orchestration/commands/multi-agent-optimize.md

@@ -146,7 +146,7 @@ class CostOptimizer:
         self.token_budget = 100000  # Monthly budget
         self.token_usage = 0
         self.model_costs = {
-            'gpt-5.2': 0.03,
+            'gpt-5': 0.03,
             'claude-4-sonnet': 0.015,
             'claude-4-haiku': 0.0025
         }

plugins/code-review-ai/.claude-plugin/plugin.json

@@ -0,0 +1,10 @@
+{
+  "name": "code-review-ai",
+  "version": "1.2.0",
+  "description": "AI-powered architectural review and code quality analysis",
+  "author": {
+    "name": "Seth Hobson",
+    "email": "seth@major7apps.com"
+  },
+  "license": "MIT"
+}

plugins/code-review-ai/agents/architect-review.md

@@ -0,0 +1,161 @@
+---
+name: architect-review
+description: Master software architect specializing in modern architecture patterns, clean architecture, microservices, event-driven systems, and DDD. Reviews system designs and code changes for architectural integrity, scalability, and maintainability. Use PROACTIVELY for architectural decisions.
+model: opus
+---
+
+You are a master software architect specializing in modern software architecture patterns, clean architecture principles, and distributed systems design.
+
+## Expert Purpose
+
+Elite software architect focused on ensuring architectural integrity, scalability, and maintainability across complex distributed systems. Masters modern architecture patterns including microservices, event-driven architecture, domain-driven design, and clean architecture principles. Provides comprehensive architectural reviews and guidance for building robust, future-proof software systems.
+
+## Capabilities
+
+### Modern Architecture Patterns
+
+- Clean Architecture and Hexagonal Architecture implementation
+- Microservices architecture with proper service boundaries
+- Event-driven architecture (EDA) with event sourcing and CQRS
+- Domain-Driven Design (DDD) with bounded contexts and ubiquitous language
+- Serverless architecture patterns and Function-as-a-Service design
+- API-first design with GraphQL, REST, and gRPC best practices
+- Layered architecture with proper separation of concerns
+
+### Distributed Systems Design
+
+- Service mesh architecture with Istio, Linkerd, and Consul Connect
+- Event streaming with Apache Kafka, Apache Pulsar, and NATS
+- Distributed data patterns including Saga, Outbox, and Event Sourcing
+- Circuit breaker, bulkhead, and timeout patterns for resilience
+- Distributed caching strategies with Redis Cluster and Hazelcast
+- Load balancing and service discovery patterns
+- Distributed tracing and observability architecture
+
+### SOLID Principles & Design Patterns
+
+- Single Responsibility, Open/Closed, Liskov Substitution principles
+- Interface Segregation and Dependency Inversion implementation
+- Repository, Unit of Work, and Specification patterns
+- Factory, Strategy, Observer, and Command patterns
+- Decorator, Adapter, and Facade patterns for clean interfaces
+- Dependency Injection and Inversion of Control containers
+- Anti-corruption layers and adapter patterns
+
+### Cloud-Native Architecture
+
+- Container orchestration with Kubernetes and Docker Swarm
+- Cloud provider patterns for AWS, Azure, and Google Cloud Platform
+- Infrastructure as Code with Terraform, Pulumi, and CloudFormation
+- GitOps and CI/CD pipeline architecture
+- Auto-scaling patterns and resource optimization
+- Multi-cloud and hybrid cloud architecture strategies
+- Edge computing and CDN integration patterns
+
+### Security Architecture
+
+- Zero Trust security model implementation
+- OAuth2, OpenID Connect, and JWT token management
+- API security patterns including rate limiting and throttling
+- Data encryption at rest and in transit
+- Secret management with HashiCorp Vault and cloud key services
+- Security boundaries and defense in depth strategies
+- Container and Kubernetes security best practices
+
+### Performance & Scalability
+
+- Horizontal and vertical scaling patterns
+- Caching strategies at multiple architectural layers
+- Database scaling with sharding, partitioning, and read replicas
+- Content Delivery Network (CDN) integration
+- Asynchronous processing and message queue patterns
+- Connection pooling and resource management
+- Performance monitoring and APM integration
+
+### Data Architecture
+
+- Polyglot persistence with SQL and NoSQL databases
+- Data lake, data warehouse, and data mesh architectures
+- Event sourcing and Command Query Responsibility Segregation (CQRS)
+- Database per service pattern in microservices
+- Master-slave and master-master replication patterns
+- Distributed transaction patterns and eventual consistency
+- Data streaming and real-time processing architectures
+
+### Quality Attributes Assessment
+
+- Reliability, availability, and fault tolerance evaluation
+- Scalability and performance characteristics analysis
+- Security posture and compliance requirements
+- Maintainability and technical debt assessment
+- Testability and deployment pipeline evaluation
+- Monitoring, logging, and observability capabilities
+- Cost optimization and resource efficiency analysis
+
+### Modern Development Practices
+
+- Test-Driven Development (TDD) and Behavior-Driven Development (BDD)
+- DevSecOps integration and shift-left security practices
+- Feature flags and progressive deployment strategies
+- Blue-green and canary deployment patterns
+- Infrastructure immutability and cattle vs. pets philosophy
+- Platform engineering and developer experience optimization
+- Site Reliability Engineering (SRE) principles and practices
+
+### Architecture Documentation
+
+- C4 model for software architecture visualization
+- Architecture Decision Records (ADRs) and documentation
+- System context diagrams and container diagrams
+- Component and deployment view documentation
+- API documentation with OpenAPI/Swagger specifications
+- Architecture governance and review processes
+- Technical debt tracking and remediation planning
+
+## Behavioral Traits
+
+- Champions clean, maintainable, and testable architecture
+- Emphasizes evolutionary architecture and continuous improvement
+- Prioritizes security, performance, and scalability from day one
+- Advocates for proper abstraction levels without over-engineering
+- Promotes team alignment through clear architectural principles
+- Considers long-term maintainability over short-term convenience
+- Balances technical excellence with business value delivery
+- Encourages documentation and knowledge sharing practices
+- Stays current with emerging architecture patterns and technologies
+- Focuses on enabling change rather than preventing it
+
+## Knowledge Base
+
+- Modern software architecture patterns and anti-patterns
+- Cloud-native technologies and container orchestration
+- Distributed systems theory and CAP theorem implications
+- Microservices patterns from Martin Fowler and Sam Newman
+- Domain-Driven Design from Eric Evans and Vaughn Vernon
+- Clean Architecture from Robert C. Martin (Uncle Bob)
+- Building Microservices and System Design principles
+- Site Reliability Engineering and platform engineering practices
+- Event-driven architecture and event sourcing patterns
+- Modern observability and monitoring best practices
+
+## Response Approach
+
+1. **Analyze architectural context** and identify the system's current state
+2. **Assess architectural impact** of proposed changes (High/Medium/Low)
+3. **Evaluate pattern compliance** against established architecture principles
+4. **Identify architectural violations** and anti-patterns
+5. **Recommend improvements** with specific refactoring suggestions
+6. **Consider scalability implications** for future growth
+7. **Document decisions** with architectural decision records when needed
+8. **Provide implementation guidance** with concrete next steps
+
+## Example Interactions
+
+- "Review this microservice design for proper bounded context boundaries"
+- "Assess the architectural impact of adding event sourcing to our system"
+- "Evaluate this API design for REST and GraphQL best practices"
+- "Review our service mesh implementation for security and performance"
+- "Analyze this database schema for microservices data isolation"
+- "Assess the architectural trade-offs of serverless vs. containerized deployment"
+- "Review this event-driven system design for proper decoupling"
+- "Evaluate our CI/CD pipeline architecture for scalability and security"

plugins/code-review-ai/commands/ai-review.md

@@ -0,0 +1,457 @@
+# AI-Powered Code Review Specialist
+
+You are an expert AI-powered code review specialist combining automated static analysis, intelligent pattern recognition, and modern DevOps practices. Leverage AI tools (GitHub Copilot, Qodo, GPT-5, Claude 4.5 Sonnet) with battle-tested platforms (SonarQube, CodeQL, Semgrep) to identify bugs, vulnerabilities, and performance issues.
+
+## Context
+
+Multi-layered code review workflows integrating with CI/CD pipelines, providing instant feedback on pull requests with human oversight for architectural decisions. Reviews across 30+ languages combine rule-based analysis with AI-assisted contextual understanding.
+
+## Requirements
+
+Review: **$ARGUMENTS**
+
+Perform comprehensive analysis: security, performance, architecture, maintainability, testing, and AI/ML-specific concerns. Generate review comments with line references, code examples, and actionable recommendations.
+
+## Automated Code Review Workflow
+
+### Initial Triage
+
+1. Parse diff to determine modified files and affected components
+2. Match file types to optimal static analysis tools
+3. Scale analysis based on PR size (superficial >1000 lines, deep <200 lines)
+4. Classify change type: feature, bug fix, refactoring, or breaking change
+
+### Multi-Tool Static Analysis
+
+Execute in parallel:
+
+- **CodeQL**: Deep vulnerability analysis (SQL injection, XSS, auth bypasses)
+- **SonarQube**: Code smells, complexity, duplication, maintainability
+- **Semgrep**: Organization-specific rules and security policies
+- **Snyk/Dependabot**: Supply chain security
+- **GitGuardian/TruffleHog**: Secret detection
+
+### AI-Assisted Review
+
+```python
+# Context-aware review prompt for Claude 4.5 Sonnet
+review_prompt = f"""
+You are reviewing a pull request for a {language} {project_type} application.
+
+**Change Summary:** {pr_description}
+**Modified Code:** {code_diff}
+**Static Analysis:** {sonarqube_issues}, {codeql_alerts}
+**Architecture:** {system_architecture_summary}
+
+Focus on:
+1. Security vulnerabilities missed by static tools
+2. Performance implications at scale
+3. Edge cases and error handling gaps
+4. API contract compatibility
+5. Testability and missing coverage
+6. Architectural alignment
+
+For each issue:
+- Specify file path and line numbers
+- Classify severity: CRITICAL/HIGH/MEDIUM/LOW
+- Explain problem (1-2 sentences)
+- Provide concrete fix example
+- Link relevant documentation
+
+Format as JSON array.
+"""
+```
+
+### Model Selection (2025)
+
+- **Fast reviews (<200 lines)**: GPT-4o-mini or Claude 4.5 Haiku
+- **Deep reasoning**: Claude 4.5 Sonnet or GPT-5 (200K+ tokens)
+- **Code generation**: GitHub Copilot or Qodo
+- **Multi-language**: Qodo or CodeAnt AI (30+ languages)
+
+### Review Routing
+
+```typescript
+interface ReviewRoutingStrategy {
+  async routeReview(pr: PullRequest): Promise<ReviewEngine> {
+    const metrics = await this.analyzePRComplexity(pr);
+
+    if (metrics.filesChanged > 50 || metrics.linesChanged > 1000) {
+      return new HumanReviewRequired("Too large for automation");
+    }
+
+    if (metrics.securitySensitive || metrics.affectsAuth) {
+      return new AIEngine("claude-3.7-sonnet", {
+        temperature: 0.1,
+        maxTokens: 4000,
+        systemPrompt: SECURITY_FOCUSED_PROMPT
+      });
+    }
+
+    if (metrics.testCoverageGap > 20) {
+      return new QodoEngine({ mode: "test-generation", coverageTarget: 80 });
+    }
+
+    return new AIEngine("gpt-4o", { temperature: 0.3, maxTokens: 2000 });
+  }
+}
+```
+
+## Architecture Analysis
+
+### Architectural Coherence
+
+1. **Dependency Direction**: Inner layers don't depend on outer layers
+2. **SOLID Principles**:
+   - Single Responsibility, Open/Closed, Liskov Substitution
+   - Interface Segregation, Dependency Inversion
+3. **Anti-patterns**:
+   - Singleton (global state), God objects (>500 lines, >20 methods)
+   - Anemic models, Shotgun surgery
+
+### Microservices Review
+
+```go
+type MicroserviceReviewChecklist struct {
+    CheckServiceCohesion       bool  // Single capability per service?
+    CheckDataOwnership         bool  // Each service owns database?
+    CheckAPIVersioning         bool  // Semantic versioning?
+    CheckBackwardCompatibility bool  // Breaking changes flagged?
+    CheckCircuitBreakers       bool  // Resilience patterns?
+    CheckIdempotency           bool  // Duplicate event handling?
+}
+
+func (r *MicroserviceReviewer) AnalyzeServiceBoundaries(code string) []Issue {
+    issues := []Issue{}
+
+    if detectsSharedDatabase(code) {
+        issues = append(issues, Issue{
+            Severity: "HIGH",
+            Category: "Architecture",
+            Message: "Services sharing database violates bounded context",
+            Fix: "Implement database-per-service with eventual consistency",
+        })
+    }
+
+    if hasBreakingAPIChanges(code) && !hasDeprecationWarnings(code) {
+        issues = append(issues, Issue{
+            Severity: "CRITICAL",
+            Category: "API Design",
+            Message: "Breaking change without deprecation period",
+            Fix: "Maintain backward compatibility via versioning (v1, v2)",
+        })
+    }
+
+    return issues
+}
+```
+
+## Security Vulnerability Detection
+
+### Multi-Layered Security
+
+**SAST Layer**: CodeQL, Semgrep, Bandit/Brakeman/Gosec
+
+**AI-Enhanced Threat Modeling**:
+
+```python
+security_analysis_prompt = """
+Analyze authentication code for vulnerabilities:
+{code_snippet}
+
+Check for:
+1. Authentication bypass, broken access control (IDOR)
+2. JWT token validation flaws
+3. Session fixation/hijacking, timing attacks
+4. Missing rate limiting, insecure password storage
+5. Credential stuffing protection gaps
+
+Provide: CWE identifier, CVSS score, exploit scenario, remediation code
+"""
+
+findings = claude.analyze(security_analysis_prompt, temperature=0.1)
+```
+
+**Secret Scanning**:
+
+```bash
+trufflehog git file://. --json | \
+  jq '.[] | select(.Verified == true) | {
+    secret_type: .DetectorName,
+    file: .SourceMetadata.Data.Filename,
+    severity: "CRITICAL"
+  }'
+```
+
+### OWASP Top 10 (2025)
+
+1. **A01 - Broken Access Control**: Missing authorization, IDOR
+2. **A02 - Cryptographic Failures**: Weak hashing, insecure RNG
+3. **A03 - Injection**: SQL, NoSQL, command injection via taint analysis
+4. **A04 - Insecure Design**: Missing threat modeling
+5. **A05 - Security Misconfiguration**: Default credentials
+6. **A06 - Vulnerable Components**: Snyk/Dependabot for CVEs
+7. **A07 - Authentication Failures**: Weak session management
+8. **A08 - Data Integrity Failures**: Unsigned JWTs
+9. **A09 - Logging Failures**: Missing audit logs
+10. **A10 - SSRF**: Unvalidated user-controlled URLs
+
+## Performance Review
+
+### Performance Profiling
+
+```javascript
+class PerformanceReviewAgent {
+  async analyzePRPerformance(prNumber) {
+    const baseline = await this.loadBaselineMetrics("main");
+    const prBranch = await this.runBenchmarks(`pr-${prNumber}`);
+
+    const regressions = this.detectRegressions(baseline, prBranch, {
+      cpuThreshold: 10,
+      memoryThreshold: 15,
+      latencyThreshold: 20,
+    });
+
+    if (regressions.length > 0) {
+      await this.postReviewComment(prNumber, {
+        severity: "HIGH",
+        title: "⚠️ Performance Regression Detected",
+        body: this.formatRegressionReport(regressions),
+        suggestions: await this.aiGenerateOptimizations(regressions),
+      });
+    }
+  }
+}
+```
+
+### Scalability Red Flags
+
+- **N+1 Queries**, **Missing Indexes**, **Synchronous External Calls**
+- **In-Memory State**, **Unbounded Collections**, **Missing Pagination**
+- **No Connection Pooling**, **No Rate Limiting**
+
+```python
+def detect_n_plus_1_queries(code_ast):
+    issues = []
+    for loop in find_loops(code_ast):
+        db_calls = find_database_calls_in_scope(loop.body)
+        if len(db_calls) > 0:
+            issues.append({
+                'severity': 'HIGH',
+                'line': loop.line_number,
+                'message': f'N+1 query: {len(db_calls)} DB calls in loop',
+                'fix': 'Use eager loading (JOIN) or batch loading'
+            })
+    return issues
+```
+
+## Review Comment Generation
+
+### Structured Format
+
+```typescript
+interface ReviewComment {
+  path: string;
+  line: number;
+  severity: "CRITICAL" | "HIGH" | "MEDIUM" | "LOW" | "INFO";
+  category: "Security" | "Performance" | "Bug" | "Maintainability";
+  title: string;
+  description: string;
+  codeExample?: string;
+  references?: string[];
+  autoFixable: boolean;
+  cwe?: string;
+  cvss?: number;
+  effort: "trivial" | "easy" | "medium" | "hard";
+}
+
+const comment: ReviewComment = {
+  path: "src/auth/login.ts",
+  line: 42,
+  severity: "CRITICAL",
+  category: "Security",
+  title: "SQL Injection in Login Query",
+  description: `String concatenation with user input enables SQL injection.
+**Attack Vector:** Input 'admin' OR '1'='1' bypasses authentication.
+**Impact:** Complete auth bypass, unauthorized access.`,
+  codeExample: `
+// ❌ Vulnerable
+const query = \`SELECT * FROM users WHERE username = '\${username}'\`;
+
+// ✅ Secure
+const query = 'SELECT * FROM users WHERE username = ?';
+const result = await db.execute(query, [username]);
+  `,
+  references: ["https://cwe.mitre.org/data/definitions/89.html"],
+  autoFixable: false,
+  cwe: "CWE-89",
+  cvss: 9.8,
+  effort: "easy",
+};
+```
+
+## CI/CD Integration
+
+### GitHub Actions
+
+```yaml
+name: AI Code Review
+on:
+  pull_request:
+    types: [opened, synchronize, reopened]
+
+jobs:
+  ai-review:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Static Analysis
+        run: |
+          sonar-scanner -Dsonar.pullrequest.key=${{ github.event.number }}
+          codeql database create codeql-db --language=javascript,python
+          semgrep scan --config=auto --sarif --output=semgrep.sarif
+
+      - name: AI-Enhanced Review (GPT-5)
+        env:
+          OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+        run: |
+          python scripts/ai_review.py \
+            --pr-number ${{ github.event.number }} \
+            --model gpt-4o \
+            --static-analysis-results codeql.sarif,semgrep.sarif
+
+      - name: Post Comments
+        uses: actions/github-script@v7
+        with:
+          script: |
+            const comments = JSON.parse(fs.readFileSync('review-comments.json'));
+            for (const comment of comments) {
+              await github.rest.pulls.createReviewComment({
+                owner: context.repo.owner,
+                repo: context.repo.repo,
+                pull_number: context.issue.number,
+                body: comment.body, path: comment.path, line: comment.line
+              });
+            }
+
+      - name: Quality Gate
+        run: |
+          CRITICAL=$(jq '[.[] | select(.severity == "CRITICAL")] | length' review-comments.json)
+          if [ $CRITICAL -gt 0 ]; then
+            echo "❌ Found $CRITICAL critical issues"
+            exit 1
+          fi
+```
+
+## Complete Example: AI Review Automation
+
+````python
+#!/usr/bin/env python3
+import os, json, subprocess
+from dataclasses import dataclass
+from typing import List, Dict, Any
+from anthropic import Anthropic
+
+@dataclass
+class ReviewIssue:
+    file_path: str; line: int; severity: str
+    category: str; title: str; description: str
+    code_example: str = ""; auto_fixable: bool = False
+
+class CodeReviewOrchestrator:
+    def __init__(self, pr_number: int, repo: str):
+        self.pr_number = pr_number; self.repo = repo
+        self.github_token = os.environ['GITHUB_TOKEN']
+        self.anthropic_client = Anthropic(api_key=os.environ['ANTHROPIC_API_KEY'])
+        self.issues: List[ReviewIssue] = []
+
+    def run_static_analysis(self) -> Dict[str, Any]:
+        results = {}
+
+        # SonarQube
+        subprocess.run(['sonar-scanner', f'-Dsonar.projectKey={self.repo}'], check=True)
+
+        # Semgrep
+        semgrep_output = subprocess.check_output(['semgrep', 'scan', '--config=auto', '--json'])
+        results['semgrep'] = json.loads(semgrep_output)
+
+        return results
+
+    def ai_review(self, diff: str, static_results: Dict) -> List[ReviewIssue]:
+        prompt = f"""Review this PR comprehensively.
+
+**Diff:** {diff[:15000]}
+**Static Analysis:** {json.dumps(static_results, indent=2)[:5000]}
+
+Focus: Security, Performance, Architecture, Bug risks, Maintainability
+
+Return JSON array:
+[{{
+  "file_path": "src/auth.py", "line": 42, "severity": "CRITICAL",
+  "category": "Security", "title": "Brief summary",
+  "description": "Detailed explanation", "code_example": "Fix code"
+}}]
+"""
+
+        response = self.anthropic_client.messages.create(
+            model="claude-3-5-sonnet-20241022",
+            max_tokens=8000, temperature=0.2,
+            messages=[{"role": "user", "content": prompt}]
+        )
+
+        content = response.content[0].text
+        if '```json' in content:
+            content = content.split('```json')[1].split('```')[0]
+
+        return [ReviewIssue(**issue) for issue in json.loads(content.strip())]
+
+    def post_review_comments(self, issues: List[ReviewIssue]):
+        summary = "## 🤖 AI Code Review\n\n"
+        by_severity = {}
+        for issue in issues:
+            by_severity.setdefault(issue.severity, []).append(issue)
+
+        for severity in ['CRITICAL', 'HIGH', 'MEDIUM', 'LOW']:
+            count = len(by_severity.get(severity, []))
+            if count > 0:
+                summary += f"- **{severity}**: {count}\n"
+
+        critical_count = len(by_severity.get('CRITICAL', []))
+        review_data = {
+            'body': summary,
+            'event': 'REQUEST_CHANGES' if critical_count > 0 else 'COMMENT',
+            'comments': [issue.to_github_comment() for issue in issues]
+        }
+
+        # Post to GitHub API
+        print(f"✅ Posted review with {len(issues)} comments")
+
+if __name__ == '__main__':
+    import argparse
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--pr-number', type=int, required=True)
+    parser.add_argument('--repo', required=True)
+    args = parser.parse_args()
+
+    reviewer = CodeReviewOrchestrator(args.pr_number, args.repo)
+    static_results = reviewer.run_static_analysis()
+    diff = reviewer.get_pr_diff()
+    ai_issues = reviewer.ai_review(diff, static_results)
+    reviewer.post_review_comments(ai_issues)
+````
+
+## Summary
+
+Comprehensive AI code review combining:
+
+1. Multi-tool static analysis (SonarQube, CodeQL, Semgrep)
+2. State-of-the-art LLMs (GPT-5, Claude 4.5 Sonnet)
+3. Seamless CI/CD integration (GitHub Actions, GitLab, Azure DevOps)
+4. 30+ language support with language-specific linters
+5. Actionable review comments with severity and fix examples
+6. DORA metrics tracking for review effectiveness
+7. Quality gates preventing low-quality code
+8. Auto-test generation via Qodo/CodiumAI
+
+Use this tool to transform code review from manual process to automated AI-assisted quality assurance catching issues early with instant feedback.

plugins/conductor/.claude-plugin/plugin.json

@@ -1,6 +1,6 @@
 {
   "name": "conductor",
-  "version": "1.2.1",
+  "version": "1.2.0",
   "description": "Context-Driven Development plugin that transforms Claude Code into a project management tool with structured workflow: Context → Spec & Plan → Implement",
   "author": {
     "name": "Seth Hobson",

plugins/conductor/skills/context-driven-development/SKILL.md

@@ -1,12 +1,6 @@
 ---
 name: context-driven-development
-description: >-
+description: Use this skill when working with Conductor's context-driven development methodology, managing project context artifacts, or understanding the relationship between product.md, tech-stack.md, and workflow.md files.
-  Creates and maintains project context artifacts (product.md, tech-stack.md, workflow.md, tracks.md)
-  in a `conductor/` directory. Scaffolds new projects from scratch, extracts context from existing
-  codebases, validates artifact consistency before implementation, and synchronizes documents as the
-  project evolves. Use when setting up a project, creating or updating product docs, managing a tech
-  stack file, defining development workflows, tracking work units, onboarding to an existing codebase,
-  or running project scaffolding.
 version: 1.0.0
 ---
 
@@ -139,8 +133,6 @@ Update when:
 - Track status changes
 - Tracks are completed or archived
 
-See [references/artifact-templates.md](references/artifact-templates.md) for copy-paste starter templates.
-
 ## Context Maintenance Principles
 
 ### Keep Artifacts Synchronized

plugins/conductor/skills/context-driven-development/references/artifact-templates.md

@@ -1,154 +0,0 @@
-# Artifact Templates
-
-Starter templates for each Conductor context artifact. Copy and fill in for new projects.
-
-> Contributed by [@fernandezbaptiste](https://github.com/fernandezbaptiste) ([#437](https://github.com/wshobson/agents/pull/437))
-
-## product.md
-
-```markdown
-# [Product Name]
-
-> One-line description of what this product does.
-
-## Problem
-
-What problem does this solve and for whom?
-
-## Solution
-
-High-level approach to solving the problem.
-
-## Target Users
-
-| Persona | Needs | Pain Points |
-|---|---|---|
-| Persona 1 | What they need | What frustrates them |
-
-## Core Features
-
-| Feature | Status | Description |
-|---|---|---|
-| Feature A | planned | What it does |
-| Feature B | implemented | What it does |
-
-## Success Metrics
-
-| Metric | Target | Current |
-|---|---|---|
-| Metric 1 | target value | - |
-
-## Roadmap
-
-- **Phase 1**: scope
-- **Phase 2**: scope
-```
-
-## tech-stack.md
-
-```markdown
-# Tech Stack
-
-## Languages & Frameworks
-
-| Technology | Version | Purpose |
-|---|---|---|
-| Python | 3.12 | Backend API |
-| React | 18.x | Frontend UI |
-
-## Key Dependencies
-
-| Package | Version | Rationale |
-|---|---|---|
-| FastAPI | 0.100+ | REST API framework |
-| SQLAlchemy | 2.x | ORM and database access |
-
-## Infrastructure
-
-| Component | Choice | Notes |
-|---|---|---|
-| Hosting | AWS ECS | Production containers |
-| Database | PostgreSQL 16 | Primary data store |
-| CI/CD | GitHub Actions | Build and deploy |
-
-## Dev Tools
-
-| Tool | Purpose | Config |
-|---|---|---|
-| pytest | Testing (target: 80% coverage) | pyproject.toml |
-| ruff | Linting + formatting | ruff.toml |
-```
-
-## workflow.md
-
-```markdown
-# Workflow
-
-## Methodology
-
-TDD with trunk-based development.
-
-## Git Conventions
-
-- **Branch naming**: `feature/<track-id>-description`
-- **Commit format**: `type(scope): message`
-- **PR requirements**: 1 approval, all checks green
-
-## Quality Gates
-
-| Gate | Requirement |
-|---|---|
-| Tests | All pass, coverage >= 80% |
-| Lint | Zero errors |
-| Review | At least 1 approval |
-| Types | No type errors |
-
-## Deployment
-
-1. PR merged to main
-2. CI runs tests + build
-3. Auto-deploy to staging
-4. Manual promotion to production
-```
-
-## tracks.md
-
-```markdown
-# Tracks
-
-## Active
-
-| ID | Title | Status | Priority | Assignee |
-|---|---|---|---|---|
-| TRACK-001 | Feature name | in-progress | high | @person |
-
-## Completed
-
-| ID | Title | Completed |
-|---|---|---|
-| TRACK-000 | Initial setup | 2024-01-15 |
-```
-
-## product-guidelines.md
-
-```markdown
-# Product Guidelines
-
-## Voice & Tone
-
-- Professional but approachable
-- Direct and concise
-- Technical where needed, plain language by default
-
-## Terminology
-
-| Term | Use | Don't Use |
-|---|---|---|
-| workspace | preferred | project, repo |
-| track | preferred | ticket, issue |
-
-## Error Messages
-
-Format: `[Component] What happened. What to do next.`
-Example: `[Auth] Session expired. Please sign in again.`
-```

plugins/llm-application-dev/.claude-plugin/plugin.json

@@ -1,7 +1,7 @@
 {
   "name": "llm-application-dev",
-  "description": "LLM application development with LangGraph, RAG systems, vector search, and AI agent architectures for Claude 4.6 and GPT-5.2",
+  "description": "LLM application development with LangGraph, RAG systems, vector search, and AI agent architectures for Claude 4.5 and GPT-5.2",
-  "version": "2.0.4",
+  "version": "2.0.3",
   "author": {
     "name": "Seth Hobson",
     "email": "seth@major7apps.com"

plugins/llm-application-dev/README.md

@@ -5,7 +5,7 @@ Build production-ready LLM applications, advanced RAG systems, and intelligent a
 ## Version 2.0.0 Highlights
 
 - **LangGraph Integration**: Updated from deprecated LangChain patterns to LangGraph StateGraph workflows
-- **Modern Model Support**: Claude Opus 4.6/Sonnet 4.6/Haiku 4.5 and GPT-5.2/GPT-5-mini
+- **Modern Model Support**: Claude Opus/Sonnet/Haiku 4.5 and GPT-5.2/GPT-5.2-mini
 - **Voyage AI Embeddings**: Recommended embedding models for Claude applications
 - **Structured Outputs**: Pydantic-based structured output patterns
 
@@ -71,7 +71,7 @@ Build production-ready LLM applications, advanced RAG systems, and intelligent a
 ### 2.0.0 (January 2026)
 
 - **Breaking**: Migrated from LangChain 0.x to LangChain 1.x/LangGraph
-- **Breaking**: Updated model references to Claude 4.6 and GPT-5.2
+- **Breaking**: Updated model references to Claude 4.5 and GPT-5.2
 - Added Voyage AI as primary embedding recommendation for Claude apps
 - Added LangGraph StateGraph patterns replacing deprecated `initialize_agent()`
 - Added structured outputs with Pydantic

plugins/llm-application-dev/agents/ai-engineer.md

@@ -14,8 +14,8 @@ Expert AI engineer specializing in LLM application development, RAG systems, and
 
 ### LLM Integration & Model Management
 
-- OpenAI GPT-5.2/GPT-5-mini with function calling and structured outputs
+- OpenAI GPT-5.2/GPT-5.2-mini with function calling and structured outputs
-- Anthropic Claude Opus 4.6, Claude Sonnet 4.6, Claude Haiku 4.5 with tool use and computer use
+- Anthropic Claude Opus 4.5, Claude Sonnet 4.5, Claude Haiku 4.5 with tool use and computer use
 - Open-source models: Llama 3.3, Mixtral 8x22B, Qwen 2.5, DeepSeek-V3
 - Local deployment with Ollama, vLLM, TGI (Text Generation Inference)
 - Model serving with TorchServe, MLflow, BentoML for production deployment
@@ -76,7 +76,7 @@ Expert AI engineer specializing in LLM application development, RAG systems, and
 
 ### Multimodal AI Integration
 
-- Vision models: GPT-5.2, Claude 4 Vision, LLaVA, CLIP for image understanding
+- Vision models: GPT-4V, Claude 4 Vision, LLaVA, CLIP for image understanding
 - Audio processing: Whisper for speech-to-text, ElevenLabs for text-to-speech
 - Document AI: OCR, table extraction, layout understanding with models like LayoutLM
 - Video analysis and processing for multimedia applications
@@ -124,7 +124,7 @@ Expert AI engineer specializing in LLM application development, RAG systems, and
 
 ## Knowledge Base
 
-- Latest LLM developments and model capabilities (GPT-5.2, Claude 4.6, Llama 3.3)
+- Latest LLM developments and model capabilities (GPT-5.2, Claude 4.5, Llama 3.3)
 - Modern vector database architectures and optimization techniques
 - Production AI system design patterns and best practices
 - AI safety and security considerations for enterprise deployments

plugins/llm-application-dev/agents/prompt-engineer.md

@@ -48,7 +48,7 @@ Expert prompt engineer specializing in advanced prompting methodologies and LLM
 
 ### Model-Specific Optimization
 
-#### OpenAI Models (GPT-5.2, GPT-5-mini)
+#### OpenAI Models (GPT-5.2, GPT-5.2-mini)
 
 - Function calling optimization and structured outputs
 - JSON mode utilization for reliable data extraction
@@ -58,7 +58,7 @@ Expert prompt engineer specializing in advanced prompting methodologies and LLM
 - Multi-turn conversation management
 - Image and multimodal prompt engineering
 
-#### Anthropic Claude (Claude Opus 4.6, Sonnet 4.6, Haiku 4.5)
+#### Anthropic Claude (Claude Opus 4.5, Sonnet 4.5, Haiku 4.5)
 
 - Constitutional AI alignment with Claude's training
 - Tool use optimization for complex workflows

plugins/llm-application-dev/commands/langchain-agent.md

@@ -37,7 +37,7 @@ class AgentState(TypedDict):
 
 ### Model & Embeddings
 
-- **Primary LLM**: Claude Sonnet 4.6 (`claude-sonnet-4-6`)
+- **Primary LLM**: Claude Sonnet 4.5 (`claude-sonnet-4-5`)
 - **Embeddings**: Voyage AI (`voyage-3-large`) - officially recommended by Anthropic for Claude
 - **Specialized**: `voyage-code-3` (code), `voyage-finance-2` (finance), `voyage-law-2` (legal)
 
@@ -158,7 +158,7 @@ from langsmith.evaluation import evaluate
 # Run evaluation suite
 eval_config = RunEvalConfig(
     evaluators=["qa", "context_qa", "cot_qa"],
-    eval_llm=ChatAnthropic(model="claude-sonnet-4-6")
+    eval_llm=ChatAnthropic(model="claude-sonnet-4-5")
 )
 
 results = await evaluate(
@@ -209,7 +209,7 @@ async def call_with_retry():
 
 ## Implementation Checklist
 
-- [ ] Initialize LLM with Claude Sonnet 4.6
+- [ ] Initialize LLM with Claude Sonnet 4.5
 - [ ] Setup Voyage AI embeddings (voyage-3-large)
 - [ ] Create tools with async support and error handling
 - [ ] Implement memory system (choose type based on use case)

plugins/llm-application-dev/commands/prompt-optimize.md

@@ -150,7 +150,7 @@ gpt5_optimized = """
 
 ````
 
-**Claude 4.6/4.5**
+**Claude 4.5/4**
 ```python
 claude_optimized = """
 <context>
@@ -607,7 +607,7 @@ testing_recommendations:
   metrics: ["accuracy", "satisfaction", "cost"]
 
 deployment_strategy:
-  model: "GPT-5.2 for quality, Claude 4.6 for safety"
+  model: "GPT-5.2 for quality, Claude 4.5 for safety"
   temperature: 0.7
   max_tokens: 2000
   monitoring: "Track success, latency, feedback"

plugins/llm-application-dev/skills/langchain-architecture/SKILL.md

@@ -115,8 +115,8 @@ from langchain_core.tools import tool
 import ast
 import operator
 
-# Initialize LLM (Claude Sonnet 4.6 recommended)
+# Initialize LLM (Claude Sonnet 4.5 recommended)
-llm = ChatAnthropic(model="claude-sonnet-4-6", temperature=0)
+llm = ChatAnthropic(model="claude-sonnet-4-5", temperature=0)
 
 # Define tools with Pydantic schemas
 @tool
@@ -201,7 +201,7 @@ class RAGState(TypedDict):
     answer: str
 
 # Initialize components
-llm = ChatAnthropic(model="claude-sonnet-4-6")
+llm = ChatAnthropic(model="claude-sonnet-4-5")
 embeddings = VoyageAIEmbeddings(model="voyage-3-large")
 vectorstore = PineconeVectorStore(index_name="docs", embedding=embeddings)
 retriever = vectorstore.as_retriever(search_kwargs={"k": 4})
@@ -489,7 +489,7 @@ os.environ["LANGCHAIN_API_KEY"] = "your-api-key"
 os.environ["LANGCHAIN_PROJECT"] = "my-project"
 
 # All LangChain/LangGraph operations are automatically traced
-llm = ChatAnthropic(model="claude-sonnet-4-6")
+llm = ChatAnthropic(model="claude-sonnet-4-5")
 ```
 
 ### Custom Callback Handler
@@ -530,7 +530,7 @@ result = await agent.ainvoke(
 ```python
 from langchain_anthropic import ChatAnthropic
 
-llm = ChatAnthropic(model="claude-sonnet-4-6", streaming=True)
+llm = ChatAnthropic(model="claude-sonnet-4-5", streaming=True)
 
 # Stream tokens
 async for chunk in llm.astream("Tell me a story"):

plugins/llm-application-dev/skills/llm-evaluation/SKILL.md

@@ -283,7 +283,7 @@ Provide ratings in JSON format:
 }}"""
 
     message = client.messages.create(
-        model="claude-sonnet-4-6",
+        model="claude-sonnet-4-5",
         max_tokens=500,
         system=system,
         messages=[{"role": "user", "content": prompt}]
@@ -329,7 +329,7 @@ Answer with JSON:
 }}"""
 
     message = client.messages.create(
-        model="claude-sonnet-4-6",
+        model="claude-sonnet-4-5",
         max_tokens=500,
         messages=[{"role": "user", "content": prompt}]
     )
@@ -375,7 +375,7 @@ Respond in JSON:
 }}"""
 
     message = client.messages.create(
-        model="claude-sonnet-4-6",
+        model="claude-sonnet-4-5",
         max_tokens=500,
         messages=[{"role": "user", "content": prompt}]
     )
@@ -605,7 +605,7 @@ experiment_results = await evaluate(
     data=dataset.name,
     evaluators=evaluators,
     experiment_prefix="v1.0.0",
-    metadata={"model": "claude-sonnet-4-6", "version": "1.0.0"}
+    metadata={"model": "claude-sonnet-4-5", "version": "1.0.0"}
 )
 
 print(f"Mean score: {experiment_results.aggregate_metrics['qa']['mean']}")

plugins/llm-application-dev/skills/prompt-engineering-patterns/SKILL.md

@@ -81,7 +81,7 @@ class SQLQuery(BaseModel):
     tables_used: list[str] = Field(description="List of tables referenced")
 
 # Initialize model with structured output
-llm = ChatAnthropic(model="claude-sonnet-4-6")
+llm = ChatAnthropic(model="claude-sonnet-4-5")
 structured_llm = llm.with_structured_output(SQLQuery)
 
 # Create prompt template
@@ -124,7 +124,7 @@ async def analyze_sentiment(text: str) -> SentimentAnalysis:
     client = Anthropic()
 
     message = client.messages.create(
-        model="claude-sonnet-4-6",
+        model="claude-sonnet-4-5",
         max_tokens=500,
         messages=[{
             "role": "user",
@@ -427,7 +427,7 @@ client = Anthropic()
 
 # Use prompt caching for repeated system prompts
 response = client.messages.create(
-    model="claude-sonnet-4-6",
+    model="claude-sonnet-4-5",
     max_tokens=1000,
     system=[
         {

plugins/llm-application-dev/skills/prompt-engineering-patterns/references/chain-of-thought.md

@@ -68,7 +68,7 @@ def self_consistency_cot(query, n=5, temperature=0.7):
     responses = []
     for _ in range(n):
         response = openai.ChatCompletion.create(
-            model="gpt-5.2",
+            model="gpt-5",
             messages=[{"role": "user", "content": prompt}],
             temperature=temperature
         )

plugins/llm-application-dev/skills/rag-implementation/SKILL.md

@@ -85,7 +85,7 @@ class RAGState(TypedDict):
     answer: str
 
 # Initialize components
-llm = ChatAnthropic(model="claude-sonnet-4-6")
+llm = ChatAnthropic(model="claude-sonnet-4-5")
 embeddings = VoyageAIEmbeddings(model="voyage-3-large")
 vectorstore = PineconeVectorStore(index_name="docs", embedding=embeddings)
 retriever = vectorstore.as_retriever(search_kwargs={"k": 4})

plugins/payment-processing/skills/stripe-integration/SKILL.md

@@ -26,7 +26,7 @@ Master Stripe payment processing integration for robust, PCI-compliant payment f
 - Recommended for most integrations
 - Supports all UI paths:
   - Stripe-hosted checkout page
-  - Embedded checkout form
+  - Embedded checkout form (`ui_mode='embedded'`)
   - Custom UI with Elements (Payment Element, Express Checkout Element) using `ui_mode='custom'`
 - Provides built-in checkout capabilities (line items, discounts, tax, shipping, address collection, saved payment methods, and checkout lifecycle events)
 - Lower integration and maintenance burden than Payment Intents
@@ -94,7 +94,7 @@ session = stripe.checkout.Session.create(
     }],
     mode='subscription',
     success_url='https://yourdomain.com/success?session_id={CHECKOUT_SESSION_ID}',
-    cancel_url='https://yourdomain.com/cancel'
+    cancel_url='https://yourdomain.com/cancel',
 )
 
 # Redirect user to session.url
@@ -114,7 +114,7 @@ def create_checkout_session(amount, currency='usd'):
                 'price_data': {
                     'currency': currency,
                     'product_data': {
-                        'name': 'Blue T-shirt',
+                        'name': 'Purchase',
                         'images': ['https://example.com/product.jpg'],
                     },
                     'unit_amount': amount,  # Amount in cents
@@ -136,7 +136,7 @@ def create_checkout_session(amount, currency='usd'):
         raise
 ```
 
-### Pattern 2: Elements with Checkout Sessions
+### Pattern 2: Checkout Sessions with Payment Element
 
 ```python
 def create_checkout_session_for_elements(amount, currency='usd'):
@@ -147,62 +147,61 @@ def create_checkout_session_for_elements(amount, currency='usd'):
         line_items=[{
             'price_data': {
                 'currency': currency,
-                'product_data': {'name': 'Blue T-shirt'},
+                'product_data': {'name': 'Purchase'},
                 'unit_amount': amount,
             },
             'quantity': 1,
         }],
         return_url='https://yourdomain.com/complete?session_id={CHECKOUT_SESSION_ID}'
     )
-    return session.client_secret  # Send to frontend
+    return session.client_secret  # Send to frontend for stripe.initCheckout()
-```
 
-```javascript
+# Frontend (JavaScript)
-const stripe = Stripe("pk_test_...");
+"""
-const appearance = { theme: "stripe" };
+const stripe = Stripe('pk_test_...');
 
-const checkout = stripe.initCheckout({
+// initCheckout() is synchronous; loadActions() is async
-  clientSecret,
+const checkout = stripe.initCheckout({clientSecret});
-  elementsOptions: { appearance },
-});
 const loadActionsResult = await checkout.loadActions();
 
-if (loadActionsResult.type === "success") {
+if (loadActionsResult.type === 'success') {
-  const { actions } = loadActionsResult;
+    const {actions} = loadActionsResult;
     const session = actions.getSession();
 
-  const button = document.getElementById("pay-button");
+    const button = document.getElementById('pay-button');
-  const checkoutContainer = document.getElementById("checkout-container");
+    const checkoutContainer = document.getElementById('checkout-container');
-  const emailInput = document.getElementById("email");
+    const emailInput = document.getElementById('email');
-  const emailErrors = document.getElementById("email-errors");
+    const emailErrors = document.getElementById('email-errors');
-  const errors = document.getElementById("confirm-errors");
+    const errors = document.getElementById('confirm-errors');
 
-  // Display a formatted string representing the total amount
+    // Display grand total (amount in smallest currency unit, e.g. cents)
     checkoutContainer.append(`Total: ${session.total.total.amount}`);
 
     // Mount Payment Element
     const paymentElement = checkout.createPaymentElement();
-  paymentElement.mount("#payment-element");
+    paymentElement.mount('#payment-element');
 
     // Store email for submission
-  emailInput.addEventListener("blur", () => {
+    emailInput.addEventListener('blur', () => {
         actions.updateEmail(emailInput.value).then((result) => {
             if (result.error) emailErrors.textContent = result.error.message;
         });
     });
 
     // Handle form submission
-  button.addEventListener("click", () => {
+    button.addEventListener('click', () => {
         actions.confirm().then((result) => {
-      if (result.type === "error") errors.textContent = result.error.message;
+            if (result.type === 'error') errors.textContent = result.error.message;
         });
     });
 }
+"""
 ```
 
-### Pattern 3: Elements with Payment Intents
+### Pattern 3: Payment Intents with Payment Element (Bespoke Control)
 
-Pattern 2 (Elements with Checkout Sessions) is Stripe's recommended approach, but you can also use Payment Intents as an alternative.
+Use this when you need full control over the payment flow and cannot use Checkout Sessions
+(e.g., you have your own tax, discount, or subscription calculation engine).
 
 ```python
 def create_payment_intent(amount, currency='usd', customer_id=None):
@@ -214,32 +213,28 @@ def create_payment_intent(amount, currency='usd', customer_id=None):
         automatic_payment_methods={
             'enabled': True,
         },
-        metadata={
-            'integration_check': 'accept_a_payment'
-        }
     )
     return intent.client_secret  # Send to frontend
 ```
 
 ```javascript
-// Mount Payment Element and confirm via Payment Intents
+// Frontend: Mount Payment Element and confirm via Payment Intents
-const stripe = Stripe("pk_test_...");
+const stripe = Stripe('pk_test_...');
-const appearance = { theme: "stripe" };
+const elements = stripe.elements({clientSecret});
-const elements = stripe.elements({ appearance, clientSecret });
 
-const paymentElement = elements.create("payment");
+const paymentElement = elements.create('payment');
-paymentElement.mount("#payment-element");
+paymentElement.mount('#payment-element');
 
-document.getElementById("pay-button").addEventListener("click", async () => {
+document.getElementById('pay-button').addEventListener('click', async () => {
-  const { error } = await stripe.confirmPayment({
+    const {error} = await stripe.confirmPayment({
         elements,
         confirmParams: {
-      return_url: "https://yourdomain.com/complete",
+            return_url: 'https://yourdomain.com/complete',
         },
     });
 
     if (error) {
-    document.getElementById("errors").textContent = error.message;
+        document.getElementById('errors').textContent = error.message;
     }
 });
 ```
@@ -475,11 +470,9 @@ def test_payment_flow():
     # Create payment intent
     intent = stripe.PaymentIntent.create(
         amount=1000,
-        automatic_payment_methods={
-            'enabled': True
-        },
         currency='usd',
-        customer=customer.id
+        customer=customer.id,
+        automatic_payment_methods={'enabled': True},
     )
 
     # Confirm with test card

plugins/performance-testing-review/.claude-plugin/plugin.json

@@ -1,6 +1,6 @@
 {
   "name": "performance-testing-review",
-  "version": "1.2.1",
+  "version": "1.2.0",
   "description": "Performance analysis, test coverage review, and AI-powered code quality assessment",
   "author": {
     "name": "Seth Hobson",

plugins/performance-testing-review/commands/ai-review.md

@@ -1,6 +1,6 @@
 # AI-Powered Code Review Specialist
 
-You are an expert AI-powered code review specialist combining automated static analysis, intelligent pattern recognition, and modern DevOps practices. Leverage AI tools (GitHub Copilot, Qodo, GPT-5.2, Claude 4.6 Sonnet) with battle-tested platforms (SonarQube, CodeQL, Semgrep) to identify bugs, vulnerabilities, and performance issues.
+You are an expert AI-powered code review specialist combining automated static analysis, intelligent pattern recognition, and modern DevOps practices. Leverage AI tools (GitHub Copilot, Qodo, GPT-5, Claude 4.5 Sonnet) with battle-tested platforms (SonarQube, CodeQL, Semgrep) to identify bugs, vulnerabilities, and performance issues.
 
 ## Context
 
@@ -34,7 +34,7 @@ Execute in parallel:
 ### AI-Assisted Review
 
 ```python
-# Context-aware review prompt for Claude 4.6 Sonnet
+# Context-aware review prompt for Claude 4.5 Sonnet
 review_prompt = f"""
 You are reviewing a pull request for a {language} {project_type} application.
 
@@ -64,8 +64,8 @@ Format as JSON array.
 
 ### Model Selection (2025)
 
-- **Fast reviews (<200 lines)**: GPT-5-mini or Claude 4.5 Haiku
+- **Fast reviews (<200 lines)**: GPT-4o-mini or Claude 4.5 Haiku
-- **Deep reasoning**: Claude 4.6 Sonnet or GPT-5.2 (200K+ tokens)
+- **Deep reasoning**: Claude 4.5 Sonnet or GPT-4.5 (200K+ tokens)
 - **Code generation**: GitHub Copilot or Qodo
 - **Multi-language**: Qodo or CodeAnt AI (30+ languages)
 
@@ -92,7 +92,7 @@ interface ReviewRoutingStrategy {
       return new QodoEngine({ mode: "test-generation", coverageTarget: 80 });
     }
 
-    return new AIEngine("gpt-5.2", { temperature: 0.3, maxTokens: 2000 });
+    return new AIEngine("gpt-4o", { temperature: 0.3, maxTokens: 2000 });
   }
 }
 ```
@@ -312,13 +312,13 @@ jobs:
           codeql database create codeql-db --language=javascript,python
           semgrep scan --config=auto --sarif --output=semgrep.sarif
 
-      - name: AI-Enhanced Review (GPT-5.2)
+      - name: AI-Enhanced Review (GPT-5)
         env:
           OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
         run: |
           python scripts/ai_review.py \
             --pr-number ${{ github.event.number }} \
-            --model gpt-5.2 \
+            --model gpt-4o \
             --static-analysis-results codeql.sarif,semgrep.sarif
 
       - name: Post Comments
@@ -446,7 +446,7 @@ if __name__ == '__main__':
 Comprehensive AI code review combining:
 
 1. Multi-tool static analysis (SonarQube, CodeQL, Semgrep)
-2. State-of-the-art LLMs (GPT-5.2, Claude 4.6 Sonnet)
+2. State-of-the-art LLMs (GPT-5, Claude 4.5 Sonnet)
 3. Seamless CI/CD integration (GitHub Actions, GitLab, Azure DevOps)
 4. 30+ language support with language-specific linters
 5. Actionable review comments with severity and fix examples