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claude-flow-tbowman01

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Enterprise-grade AI agent orchestration with ruv-swarm integration (Alpha Release)

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--- name: sparc description: Execute SPARC methodology workflows with batchtools optimization --- # SPARC Development Methodology (Batchtools Optimized) SPARC with batchtools enables parallel execution of development phases, concurrent multi-mode operations, and efficient batch processing across the entire development lifecycle. ## Enhanced SPARC Modes with Batch Capabilities ### Core Development Modes (Parallelized) - `/sparc-architect` - ๐Ÿ—๏ธ Parallel architecture design across components - `/sparc-code` - ๐Ÿง  Concurrent auto-coding for multiple modules - `/sparc-tdd` - ๐Ÿงช Parallel test suite development - `/sparc-debug` - ๐Ÿชฒ Concurrent debugging across systems - `/sparc-security-review` - ๐Ÿ›ก๏ธ Parallel security analysis - `/sparc-docs-writer` - ๐Ÿ“š Batch documentation generation - `/sparc-integration` - ๐Ÿ”— Parallel system integration - `/sparc-refinement-optimization-mode` - ๐Ÿงน Concurrent optimization ### Batch Mode Operations - `/sparc-batch` - ๐Ÿš€ Execute multiple modes in parallel - `/sparc-pipeline` - ๐Ÿ“Š Pipeline mode execution - `/sparc-distributed` - ๐ŸŒ Distributed SPARC processing - `/sparc-concurrent` - โšก Concurrent phase execution ## Batch Quick Start ### Parallel Mode Execution: ```bash # Execute multiple modes concurrently npx claude-flow sparc batch-run --modes '{ "architect": "Design user service", "code": "Implement auth module", "tdd": "Create test suite", "docs": "Generate API documentation" }' --parallel # Pipeline execution with dependencies npx claude-flow sparc pipeline --stages '[ { "mode": "spec-pseudocode", "tasks": ["auth", "user", "api"] }, { "mode": "architect", "depends": ["spec-pseudocode"] }, { "mode": "tdd", "parallel": true }, { "mode": "code", "depends": ["tdd"] } ]' ``` ### Batch TDD Workflow: ```bash # Parallel TDD for multiple features npx claude-flow sparc batch-tdd --features '{ "authentication": { "priority": "high", "coverage": "95%" }, "user-management": { "priority": "medium", "coverage": "90%" }, "api-gateway": { "priority": "high", "coverage": "95%" } }' --parallel --monitor ``` ### Concurrent Analysis: ```bash # Analyze multiple components in parallel npx claude-flow sparc batch-analyze --components '{ "frontend": ["architecture", "performance", "security"], "backend": ["architecture", "performance", "security", "scalability"], "database": ["schema", "performance", "security"] }' --concurrent --report ``` ## Enhanced SPARC Workflow with Parallelization ### 1. **Parallel Specification Phase** ```bash # Define specifications for multiple components concurrently npx claude-flow sparc batch-spec --components '[ { "name": "auth-service", "requirements": "OAuth2, JWT, MFA" }, { "name": "user-service", "requirements": "CRUD, profiles, preferences" }, { "name": "notification-service", "requirements": "email, SMS, push" } ]' --parallel --validate ``` ### 2. **Concurrent Pseudocode Development** ```bash # Generate pseudocode for multiple algorithms npx claude-flow sparc batch-pseudocode --algorithms '{ "data-processing": ["sorting", "filtering", "aggregation"], "authentication": ["login", "refresh", "logout"], "caching": ["get", "set", "invalidate"] }' --optimize --parallel ``` ### 3. **Distributed Architecture Design** ```bash # Design architecture for microservices in parallel npx claude-flow sparc distributed-architect --services '[ "auth", "user", "product", "order", "payment", "notification" ]' --patterns "microservices" --concurrent --visualize ``` ### 4. **Massive Parallel TDD Implementation** ```bash # Execute TDD across multiple modules npx claude-flow sparc parallel-tdd --config '{ "modules": { "core": { "tests": 50, "workers": 3 }, "api": { "tests": 100, "workers": 5 }, "ui": { "tests": 75, "workers": 4 } }, "coverage": { "target": "95%", "strict": true } }' --watch --report ``` ### 5. **Batch Integration & Validation** ```bash # Integrate and validate multiple components npx claude-flow sparc batch-integrate --components '[ { "name": "frontend", "deps": ["api"] }, { "name": "api", "deps": ["database", "cache"] }, { "name": "workers", "deps": ["queue", "storage"] } ]' --test --validate --parallel ``` ## Advanced Batch Memory Integration ### Parallel Memory Operations ```bash # Store analysis results concurrently npx claude-flow sparc batch-memory-store --data '{ "arch_decisions": { "namespace": "architecture", "parallel": true }, "test_results": { "namespace": "testing", "compress": true }, "perf_metrics": { "namespace": "performance", "index": true } }' # Query across multiple namespaces npx claude-flow sparc batch-memory-query --queries '[ { "pattern": "auth*", "namespace": "specs" }, { "pattern": "test*", "namespace": "testing" }, { "pattern": "perf*", "namespace": "metrics" } ]' --parallel --aggregate ``` ## Batch Swarm Integration ### Multi-Mode Swarm Execution ```bash # Complex project with parallel SPARC modes npx claude-flow sparc swarm-batch --project "enterprise-app" --config '{ "phases": [ { "name": "design", "modes": ["spec-pseudocode", "architect"], "parallel": true, "agents": 6 }, { "name": "implementation", "modes": ["tdd", "code", "integration"], "parallel": true, "agents": 10 }, { "name": "quality", "modes": ["security-review", "optimization", "docs"], "parallel": true, "agents": 5 } ] }' --monitor --checkpoint ``` ## Performance Optimization Features ### Intelligent Work Distribution ```bash # Distribute SPARC tasks based on complexity npx claude-flow sparc distribute --analysis '{ "complexity": { "weight": 0.4, "method": "cyclomatic" }, "dependencies": { "weight": 0.3, "method": "graph" }, "priority": { "weight": 0.3, "method": "user-defined" } }' --balance --monitor ``` ### Caching and Memoization ```bash # Enable smart caching for SPARC operations npx claude-flow sparc cache-config --settings '{ "specifications": { "ttl": "7d", "size": "100MB" }, "architecture": { "ttl": "3d", "size": "500MB" }, "test-results": { "ttl": "1d", "size": "1GB" }, "code-analysis": { "ttl": "1h", "size": "2GB" } }' --optimize ``` ## Complex Workflow Examples ### Enterprise Application Development ```bash # Full SPARC workflow with maximum parallelization npx claude-flow sparc enterprise-flow --project "fintech-platform" --parallel-config '{ "specification": { "teams": ["payments", "accounts", "reporting", "compliance"], "parallel": true, "duration": "2d" }, "architecture": { "components": 15, "parallel": true, "review-cycles": 3 }, "implementation": { "modules": 50, "parallel-factor": 10, "tdd-coverage": "95%" }, "integration": { "environments": ["dev", "staging", "prod"], "parallel-deploy": true } }' --monitor --report --checkpoint ``` ### Microservices Migration ```bash # Parallel SPARC-driven migration npx claude-flow sparc migrate-batch --from "monolith" --to "microservices" --strategy '{ "analysis": { "parallel": 5, "tools": ["dependency", "complexity", "coupling"] }, "decomposition": { "parallel": 3, "method": "domain-driven" }, "implementation": { "parallel": 10, "pattern": "strangler-fig" }, "validation": { "parallel": 5, "tests": ["unit", "integration", "e2e"] } }' --rollback-enabled ``` ### AI/ML Pipeline Development ```bash # SPARC for ML pipeline with parallel processing npx claude-flow sparc ml-pipeline --config '{ "data-pipeline": { "stages": ["ingestion", "cleaning", "transformation", "validation"], "parallel": 4 }, "model-development": { "experiments": 20, "parallel": 5, "frameworks": ["tensorflow", "pytorch", "scikit-learn"] }, "deployment": { "targets": ["api", "batch", "streaming"], "parallel": true } }' --gpu-enabled --distributed ``` ## Monitoring and Analytics ### Real-time Batch Monitoring ```bash # Monitor all SPARC operations npx claude-flow sparc monitor-batch --dashboards '[ "specification-progress", "architecture-reviews", "tdd-coverage", "integration-status", "performance-metrics" ]' --real-time --alerts ``` ### Performance Analytics ```bash # Analyze SPARC workflow efficiency npx claude-flow sparc analyze-performance --metrics '{ "throughput": ["tasks/hour", "loc/day"], "quality": ["bug-density", "test-coverage"], "efficiency": ["reuse-ratio", "automation-level"] }' --compare-baseline --recommendations ```