# Real-World Use Case Examples Comprehensive examples of Anthropic architectures for common use cases, with detailed implementation guidance. ## Table of Contents 1. [Code Quality & Review](#code-quality--review) 2. [Feature Development](#feature-development) 3. [Documentation](#documentation) 4. [Testing & QA](#testing--qa) 5. [Refactoring & Modernization](#refactoring--modernization) 6. [Security & Compliance](#security--compliance) 7. [DevOps & Automation](#devops--automation) 8. [Data Analysis](#data-analysis) 9. [Customer Support](#customer-support) 10. [Content Generation](#content-generation) --- ## Code Quality & Review ### Use Case 1: Automated Code Review System **Requirements:** - Review all PRs automatically - Check coding standards - Identify security issues - Suggest improvements - Team-wide consistency **Complexity Analysis:** - Task Complexity: 6 (structured workflow) - Reusability: 8 (organization-wide) - Context: 5 (needs coding standards) - Security: 5 (read operations) **Recommended Architecture:** **Skills + Direct Prompts** **Implementation:** **1. Create code-review-expert skill:** ``` code-review-expert/ ├── SKILL.md ├── references/ │ ├── coding_standards.md │ ├── security_patterns.md │ ├── performance_guidelines.md │ └── review_checklist.md └── scripts/ └── review_pr.sh ``` **2. Usage for PRs:** ``` Simple PR (< 50 lines): → Direct Prompt "Using code-review-expert skill, review PR #123" Complex PR (> 500 lines): → Agent + Skill Review Agent: - Load code-review-expert skill - Analyze all changed files - Generate comprehensive review ``` **3. coding_standards.md:** ```markdown # Team Coding Standards ## TypeScript - Use strict mode - Explicit return types - No `any` types - Prefer const over let - 100 character line limit ## Patterns - Repository pattern for data access - Dependency injection for services - Factory pattern for object creation ## Security - Validate all inputs - Sanitize user data - Use parameterized queries - Never log sensitive data ``` **4. Review Workflow:** ```bash #!/bin/bash # review_pr.sh PR_NUMBER=$1 echo "Reviewing PR #$PR_NUMBER..." # Get PR diff gh pr diff $PR_NUMBER > /tmp/pr_diff.txt # Review with Claude + skill claude "Using code-review-expert skill, review this PR: Changes: $(cat /tmp/pr_diff.txt) Check for: 1. Coding standards compliance 2. Security vulnerabilities 3. Performance issues 4. Best practices adherence 5. Test coverage Format: Provide detailed review with specific line numbers and suggestions." ``` **Benefits:** - Consistent reviews - Team standards enforced - Reusable across all PRs - Fast feedback **Metrics:** - Review time: 2-5 minutes - Coverage: 100% of PRs - False positives: < 5% - Developer satisfaction: High --- ### Use Case 2: Code Quality Dashboard **Requirements:** - Analyze entire codebase - Track metrics over time - Identify problem areas - Generate reports **Recommended Architecture:** **Parallel Agents** **Implementation:** ``` Quality Dashboard Workflow Coordinator Agent │ ├─┬─ Complexity Agent → Analyze code complexity │ │ │ ├─ Coverage Agent → Check test coverage │ │ │ ├─ Security Agent → Find vulnerabilities │ │ │ └─ Duplication Agent → Detect code duplication │ └─→ Dashboard Agent → Generate visual report All agents run in parallel → 4x faster ``` **Code:** ```typescript // Launch parallel agents const [ complexityReport, coverageReport, securityReport, duplicationReport ] = await Promise.all([ analyzeComplexity(codebase), analyzeCoverage(codebase), analyzeSecurity(codebase), analyzeDuplication(codebase) ]); // Aggregate results const dashboard = generateDashboard({ complexity: complexityReport, coverage: coverageReport, security: securityReport, duplication: duplicationReport }); ``` --- ## Feature Development ### Use Case 3: Full-Stack Feature Implementation **Requirements:** - Implement user authentication - Frontend + Backend + Database - Tests and documentation - Deploy to staging **Recommended Architecture:** **Specialist Agent Team + Skills** **Implementation:** ``` Project Lead Agent │ ├── Frontend Agent │ Load: frontend-designer-skill │ Tasks: │ - Create login/signup components │ - Add form validation │ - Implement token storage │ - Add loading states │ ├── Backend Agent │ Load: api-design-expert-skill │ Tasks: │ - Create auth endpoints │ - Implement JWT generation │ - Add refresh token logic │ - Database queries │ ├── Database Agent │ Load: database-expert-skill │ Tasks: │ - Design user schema │ - Create migrations │ - Add indexes │ - Seed test data │ ├── Testing Agent │ Load: testing-strategies-skill │ Tasks: │ - Unit tests │ - Integration tests │ - E2E tests │ - Coverage reports │ └── DevOps Agent Load: deployment-expert-skill Tasks: - Update configs - Deploy to staging - Run smoke tests - Monitor deployment ``` **Execution:** ``` Phase 1: Planning (Sequential) Lead Agent creates detailed plan Phase 2: Implementation (Parallel) All specialist agents work simultaneously - Frontend: 15 minutes - Backend: 15 minutes - Database: 10 minutes - Tests: 20 minutes Total: 20 minutes (vs 70 minutes sequential) Phase 3: Integration (Sequential) Lead Agent coordinates integration Phase 4: Deployment (Sequential) DevOps Agent deploys to staging ``` **Benefits:** - Parallel execution (70% faster) - Specialized expertise per layer - Comprehensive test coverage - Automated deployment --- ### Use Case 4: Feature Flag System **Requirements:** - Add feature flag capability - Minimal risk implementation - Gradual rollout support - Analytics integration **Recommended Architecture:** **Skills + Multi-Phase Agents** **Implementation:** ``` Phase 1: Exploration Agent Tools: [Read, Grep, Glob] Load: architecture-patterns-skill Task: - Analyze current architecture - Identify integration points - Research feature flag patterns - Assess risk areas Phase 2: Design Agent Tools: [TodoWrite] Load: system-design-skill Task: - Design feature flag service - Plan database schema - Define API contracts - Create rollout strategy Phase 3: Implementation Agent Tools: [Read, Edit, Write] Load: coding-standards-skill Task: - Implement feature flag service - Add database migrations - Create admin UI - Write documentation Phase 4: Testing Agent Tools: [Bash, Read] Load: testing-strategies-skill Task: - Unit tests - Integration tests - Load testing - Rollback testing Phase 5: Deployment Agent Tools: [Bash] Load: deployment-patterns-skill Confirmations: ['deployment', 'database migration'] Task: - Deploy to staging - Run validation tests - Deploy to production (10% users) - Monitor metrics ``` --- ## Documentation ### Use Case 5: API Documentation Generator **Requirements:** - Generate API docs from code - Include examples - Keep docs in sync with code - Multiple output formats **Recommended Architecture:** **Skills** **Implementation:** ``` api-documentation-skill/ ├── SKILL.md ├── references/ │ ├── openapi_spec.md │ ├── documentation_guidelines.md │ └── example_formats.md ├── templates/ │ ├── endpoint_template.md │ ├── schema_template.md │ └── example_template.md └── scripts/ └── generate_docs.sh ``` **Usage:** ``` Using api-documentation-skill, generate complete API documentation for all endpoints in src/api/ Include: - OpenAPI spec - Request/response examples - Authentication details - Error responses - Rate limiting info Format: Markdown with code examples ``` **Output:** ```markdown # User API ## POST /api/users Create a new user account. ### Request ```json { "email": "user@example.com", "password": "SecurePass123!", "name": "John Doe" } ``` ### Response (201 Created) ```json { "id": "usr_123", "email": "user@example.com", "name": "John Doe", "createdAt": "2025-01-15T10:30:00Z" } ``` ### Errors - 400: Invalid email format - 409: Email already exists - 429: Rate limit exceeded ``` --- ### Use Case 6: Onboarding Documentation **Requirements:** - Help new developers get started - Multiple learning paths - Interactive tutorials - Up-to-date with codebase **Recommended Architecture:** **Progressive Disclosure Skill** **Implementation:** ``` onboarding-guide/ ├── SKILL.md ├── index.md (learning paths) ├── getting_started/ │ ├── day_1.md │ ├── day_2.md │ └── week_1.md ├── by_role/ │ ├── frontend_dev.md │ ├── backend_dev.md │ └── fullstack_dev.md ├── by_topic/ │ ├── architecture.md │ ├── deployment.md │ └── testing.md └── interactive/ ├── setup_walkthrough.sh └── first_pr_guide.sh ``` **Progressive Disclosure:** ``` New developer: "I'm a frontend developer, where do I start?" 1. Load: index.md → Shows: Learning paths 2. Load: by_role/frontend_dev.md → Shows: Frontend-specific onboarding 3. Load: getting_started/day_1.md → Shows: Day 1 tasks 4. As they progress: → Load additional topics on demand ``` --- ## Testing & QA ### Use Case 7: Comprehensive Test Suite Generator **Requirements:** - Generate tests for new features - Multiple test types - High coverage targets - Integration with CI/CD **Recommended Architecture:** **Agent + Skills** **Implementation:** ``` Test Generation Agent │ Load Skills: ├── testing-strategies-skill └── code-analysis-skill Workflow: 1. Analyze code to test 2. Identify test scenarios 3. Generate unit tests 4. Generate integration tests 5. Generate E2E tests 6. Verify coverage > 80% ``` **Example:** ``` Using testing-strategies-skill, generate comprehensive test suite for UserService class: Coverage requirements: - Unit tests: 90%+ - Integration tests: All API endpoints - E2E tests: Critical user flows Test frameworks: - Jest for unit/integration - Playwright for E2E Include: - Happy paths - Error cases - Edge cases - Security tests ``` **Generated Output:** ```typescript // user-service.test.ts describe('UserService', () => { describe('createUser', () => { it('should create user with valid data', async () => { // Test implementation }); it('should reject invalid email', async () => { // Test implementation }); it('should reject duplicate email', async () => { // Test implementation }); it('should hash password', async () => { // Test implementation }); }); // ... more tests }); ``` --- ### Use Case 8: Regression Test Suite Maintenance **Requirements:** - Keep tests up-to-date - Remove obsolete tests - Update for API changes - Improve flaky tests **Recommended Architecture:** **Multi-Phase Agents** **Implementation:** ``` Phase 1: Analysis Agent - Identify failing tests - Find flaky tests - Detect obsolete tests - Check coverage gaps Phase 2: Cleanup Agent - Remove obsolete tests - Update outdated assertions - Fix broken imports Phase 3: Enhancement Agent - Improve flaky tests - Add missing test cases - Increase coverage Phase 4: Validation Agent - Run full test suite - Verify improvements - Generate report ``` --- ## Refactoring & Modernization ### Use Case 9: Legacy Code Modernization **Requirements:** - Upgrade from JavaScript to TypeScript - Update deprecated APIs - Improve code quality - Maintain functionality **Recommended Architecture:** **Multi-Phase Agents + Skills** **Implementation:** ``` Modernization Pipeline Phase 1: Assessment Agent Load: code-quality-skill - Analyze current codebase - Identify modernization opportunities - Assess risk levels - Create priority list Phase 2: Planning Agent Load: refactoring-patterns-skill - Create detailed migration plan - Define phases and milestones - Identify dependencies - Plan rollback strategy Phase 3: TypeScript Migration Agent Load: typescript-migration-skill - Convert .js to .ts - Add type definitions - Fix type errors - Update build config Phase 4: API Update Agent Load: api-modernization-skill - Replace deprecated APIs - Update to new patterns - Modernize syntax - Optimize performance Phase 5: Testing Agent Load: testing-strategies-skill - Run existing tests - Add new tests - Verify functionality - Check performance Phase 6: Validation Agent - Compare behavior (before/after) - Run regression tests - Performance benchmarks - Generate migration report ``` **Safety Measures:** ``` - Git branch per phase - Tests after each phase - Rollback capability - Progressive rollout - Monitoring and alerts ``` --- ### Use Case 10: Microservices Extraction **Requirements:** - Extract service from monolith - Minimal downtime - Data migration - Gradual rollout **Recommended Architecture:** **SDK Custom Workflow** **Implementation:** ```typescript const microserviceExtraction = { phases: [ { name: 'Analysis', agent: analysisAgent, tasks: [ 'Identify service boundaries', 'Map dependencies', 'Plan data separation', 'Design API contracts' ] }, { name: 'Preparation', agent: prepAgent, tasks: [ 'Create new service structure', 'Set up database', 'Implement API', 'Add monitoring' ] }, { name: 'Migration', agent: migrationAgent, confirmations: ['database migration', 'traffic routing'], tasks: [ 'Migrate data', 'Deploy service', 'Route 10% traffic', 'Monitor metrics' ] }, { name: 'Validation', agent: validationAgent, tasks: [ 'Compare responses', 'Check performance', 'Verify data consistency', 'Gradual increase to 100%' ] } ] }; ``` --- ## Security & Compliance ### Use Case 11: Security Audit System **Requirements:** - Automated security scans - OWASP compliance - Vulnerability detection - Remediation guidance **Recommended Architecture:** **Specialist Agents + Security Skill** **Implementation:** ``` Security Audit Coordinator │ ├── OWASP Scanner Agent │ Load: owasp-security-skill │ Check: OWASP Top 10 vulnerabilities │ ├── Dependency Scanner Agent │ Load: dependency-security-skill │ Check: Vulnerable dependencies │ ├── Code Scanner Agent │ Load: secure-coding-skill │ Check: Code vulnerabilities │ ├── Config Scanner Agent │ Load: secure-config-skill │ Check: Insecure configurations │ └── Report Agent Aggregate: All findings Prioritize: By severity Recommend: Remediation steps ``` **Security Skill Structure:** ``` owasp-security-skill/ ├── SKILL.md ├── references/ │ ├── owasp_top_10_2024.md │ ├── vulnerability_patterns.md │ ├── remediation_guides.md │ └── secure_coding_practices.md └── checklist/ ├── injection.md ├── authentication.md ├── sensitive_data.md └── ... ``` --- ## DevOps & Automation ### Use Case 12: CI/CD Pipeline Generator **Requirements:** - Generate CI/CD pipelines - Multiple platforms (GitHub, GitLab, etc.) - Best practices built-in - Customizable workflows **Recommended Architecture:** **Skills** **Implementation:** ``` cicd-generator-skill/ ├── SKILL.md ├── references/ │ ├── pipeline_patterns.md │ ├── best_practices.md │ └── optimization_tips.md ├── templates/ │ ├── github_actions/ │ │ ├── basic.yml │ │ ├── advanced.yml │ │ └── monorepo.yml │ ├── gitlab_ci/ │ └── jenkins/ └── scripts/ └── generate_pipeline.sh ``` **Usage:** ``` Using cicd-generator-skill, generate GitHub Actions pipeline for: Project type: Node.js API Requirements: - Lint on PR - Run tests (unit, integration) - Build Docker image - Deploy to staging (on main branch) - Deploy to production (on release tag) - Security scanning - Code coverage reports Include: - Caching for faster builds - Parallel jobs where possible - Proper secrets management ``` **Generated Pipeline:** ```yaml name: CI/CD Pipeline on: pull_request: branches: [main] push: branches: [main] tags: ['v*'] jobs: lint: runs-on: ubuntu-latest steps: - uses: actions/checkout@v3 - uses: actions/setup-node@v3 with: node-version: '18' cache: 'npm' - run: npm ci - run: npm run lint test: runs-on: ubuntu-latest steps: - uses: actions/checkout@v3 - uses: actions/setup-node@v3 with: node-version: '18' cache: 'npm' - run: npm ci - run: npm test -- --coverage - uses: codecov/codecov-action@v3 security: runs-on: ubuntu-latest steps: - uses: actions/checkout@v3 - run: npm audit - uses: snyk/actions/node@master # ... more jobs ``` --- ## Data Analysis ### Use Case 13: Log Analysis and Insights **Requirements:** - Analyze application logs - Identify patterns - Detect anomalies - Generate insights **Recommended Architecture:** **Agents + Progressive Disclosure Skill** **Implementation:** ``` Log Analysis Pipeline 1. Collection Agent - Gather logs from various sources - Normalize formats - Filter relevant entries 2. Pattern Recognition Agent Load: log-analysis-patterns-skill - Identify error patterns - Find performance bottlenecks - Detect security threats - Track user behavior 3. Anomaly Detection Agent - Compare against baselines - Flag unusual patterns - Assess severity 4. Insights Agent - Aggregate findings - Generate recommendations - Create visualizations - Prioritize actions ``` **Log Analysis Skill:** ``` log-analysis-patterns-skill/ ├── patterns/ │ ├── error_patterns.md │ ├── performance_patterns.md │ ├── security_patterns.md │ └── user_behavior_patterns.md └── insights/ ├── common_issues.md └── remediation_steps.md ``` --- ## Content Generation ### Use Case 14: Technical Blog Post Generator **Requirements:** - Generate blog posts from features - SEO optimized - Brand voice consistency - Code examples included **Recommended Architecture:** **Skills** **Implementation:** ``` technical-blog-generator-skill/ ├── SKILL.md ├── references/ │ ├── brand_voice.md │ ├── seo_guidelines.md │ ├── blog_structure.md │ └── code_example_formats.md ├── templates/ │ ├── feature_announcement.md │ ├── tutorial.md │ ├── deep_dive.md │ └── comparison.md └── examples/ └── published_posts.md ``` **Usage:** ``` Using technical-blog-generator-skill, create a blog post about our new API rate limiting feature: Target audience: Backend developers Tone: Technical but accessible Include: - Why rate limiting matters - How to implement - Code examples (Node.js, Python) - Best practices - Common pitfalls SEO keywords: API rate limiting, request throttling, API security ``` --- ## Summary **Key Patterns by Use Case:** | Use Case | Architecture | Why | |----------|-------------|-----| | Code Review | Skills + Prompts | Reusable standards, simple workflow | | Feature Development | Specialist Agents + Skills | Complex, multi-layer, parallel work | | Documentation | Progressive Disclosure Skill | Large knowledge base, context efficiency | | Testing | Agents + Skills | Autonomous generation, quality standards | | Refactoring | Multi-Phase Agents | Complex, risky, needs validation | | Security | Specialist Agents + Skills | Multiple scan types, expertise needed | | CI/CD | Skills | Template generation, best practices | | Data Analysis | Agents + Skills | Pattern recognition, insights | | Content | Skills | Brand consistency, SEO requirements | **Decision Framework:** 1. Analyze your requirements 2. Match to similar use case 3. Adapt architecture pattern 4. Implement and iterate 5. Measure and optimize **Remember:** These are starting points. Adapt based on your specific needs and constraints.