Ruflo stream-chain
Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
git clone https://github.com/ruvnet/ruflo
T=$(mktemp -d) && git clone --depth=1 https://github.com/ruvnet/ruflo "$T" && mkdir -p ~/.claude/skills && cp -r "$T/.agents/skills/stream-chain" ~/.claude/skills/ruvnet-ruflo-stream-chain && rm -rf "$T"
.agents/skills/stream-chain/SKILL.mdStream-Chain Skill
Execute sophisticated multi-step workflows where each agent's output flows into the next, enabling complex data transformations and sequential processing pipelines.
Overview
Stream-Chain provides two powerful modes for orchestrating multi-agent workflows:
- Custom Chains (
): Execute custom prompt sequences with full controlrun - Predefined Pipelines (
): Use battle-tested workflows for common taskspipeline
Each step in a chain receives the complete output from the previous step, enabling sophisticated multi-agent coordination through streaming data flow.
Quick Start
Run a Custom Chain
claude-flow stream-chain run \ "Analyze codebase structure" \ "Identify improvement areas" \ "Generate action plan"
Execute a Pipeline
claude-flow stream-chain pipeline analysis
Custom Chains (run
)
runExecute custom stream chains with your own prompts for maximum flexibility.
Syntax
claude-flow stream-chain run <prompt1> <prompt2> [...] [options]
Requirements:
- Minimum 2 prompts required
- Each prompt becomes a step in the chain
- Output flows sequentially through all steps
Options
| Option | Description | Default |
|---|---|---|
| Show detailed execution information | |
| Timeout per step | |
| Enable debug mode with full logging | |
How Context Flows
Each step receives the previous output as context:
Step 1: "Write a sorting function" Output: [function implementation] Step 2 receives: "Previous step output: [function implementation] Next task: Add comprehensive tests" Step 3 receives: "Previous steps output: [function + tests] Next task: Optimize performance"
Examples
Basic Development Chain
claude-flow stream-chain run \ "Write a user authentication function" \ "Add input validation and error handling" \ "Create unit tests with edge cases"
Security Audit Workflow
claude-flow stream-chain run \ "Analyze authentication system for vulnerabilities" \ "Identify and categorize security issues by severity" \ "Propose fixes with implementation priority" \ "Generate security test cases" \ --timeout 45 \ --verbose
Code Refactoring Chain
claude-flow stream-chain run \ "Identify code smells in src/ directory" \ "Create refactoring plan with specific changes" \ "Apply refactoring to top 3 priority items" \ "Verify refactored code maintains behavior" \ --debug
Data Processing Pipeline
claude-flow stream-chain run \ "Extract data from API responses" \ "Transform data into normalized format" \ "Validate data against schema" \ "Generate data quality report"
Predefined Pipelines (pipeline
)
pipelineExecute battle-tested workflows optimized for common development tasks.
Syntax
claude-flow stream-chain pipeline <type> [options]
Available Pipelines
1. Analysis Pipeline
Comprehensive codebase analysis and improvement identification.
claude-flow stream-chain pipeline analysis
Workflow Steps:
- Structure Analysis: Map directory structure and identify components
- Issue Detection: Find potential improvements and problems
- Recommendations: Generate actionable improvement report
Use Cases:
- New codebase onboarding
- Technical debt assessment
- Architecture review
- Code quality audits
2. Refactor Pipeline
Systematic code refactoring with prioritization.
claude-flow stream-chain pipeline refactor
Workflow Steps:
- Candidate Identification: Find code needing refactoring
- Prioritization: Create ranked refactoring plan
- Implementation: Provide refactored code for top priorities
Use Cases:
- Technical debt reduction
- Code quality improvement
- Legacy code modernization
- Design pattern implementation
3. Test Pipeline
Comprehensive test generation with coverage analysis.
claude-flow stream-chain pipeline test
Workflow Steps:
- Coverage Analysis: Identify areas lacking tests
- Test Design: Create test cases for critical functions
- Implementation: Generate unit tests with assertions
Use Cases:
- Increasing test coverage
- TDD workflow support
- Regression test creation
- Quality assurance
4. Optimize Pipeline
Performance optimization with profiling and implementation.
claude-flow stream-chain pipeline optimize
Workflow Steps:
- Profiling: Identify performance bottlenecks
- Strategy: Analyze and suggest optimization approaches
- Implementation: Provide optimized code
Use Cases:
- Performance improvement
- Resource optimization
- Scalability enhancement
- Latency reduction
Pipeline Options
| Option | Description | Default |
|---|---|---|
| Show detailed execution | |
| Timeout per step | |
| Enable debug mode | |
Pipeline Examples
Quick Analysis
claude-flow stream-chain pipeline analysis
Extended Refactoring
claude-flow stream-chain pipeline refactor --timeout 60 --verbose
Debug Test Generation
claude-flow stream-chain pipeline test --debug
Comprehensive Optimization
claude-flow stream-chain pipeline optimize --timeout 90 --verbose
Pipeline Output
Each pipeline execution provides:
- Progress: Step-by-step execution status
- Results: Success$failure per step
- Timing: Total and per-step execution time
- Summary: Consolidated results and recommendations
Custom Pipeline Definitions
Define reusable pipelines in
.claude-flow$config.json:
Configuration Format
{ "streamChain": { "pipelines": { "security": { "name": "Security Audit Pipeline", "description": "Comprehensive security analysis", "prompts": [ "Scan codebase for security vulnerabilities", "Categorize issues by severity (critical$high$medium$low)", "Generate fixes with priority and implementation steps", "Create security test suite" ], "timeout": 45 }, "documentation": { "name": "Documentation Generation Pipeline", "prompts": [ "Analyze code structure and identify undocumented areas", "Generate API documentation with examples", "Create usage guides and tutorials", "Build architecture diagrams and flow charts" ] } } } }
Execute Custom Pipeline
claude-flow stream-chain pipeline security claude-flow stream-chain pipeline documentation
Advanced Use Cases
Multi-Agent Coordination
Chain different agent types for complex workflows:
claude-flow stream-chain run \ "Research best practices for API design" \ "Design REST API with discovered patterns" \ "Implement API endpoints with validation" \ "Generate OpenAPI specification" \ "Create integration tests" \ "Write deployment documentation"
Data Transformation Pipeline
Process and transform data through multiple stages:
claude-flow stream-chain run \ "Extract user data from CSV files" \ "Normalize and validate data format" \ "Enrich data with external API calls" \ "Generate analytics report" \ "Create visualization code"
Code Migration Workflow
Systematic code migration with validation:
claude-flow stream-chain run \ "Analyze legacy codebase dependencies" \ "Create migration plan with risk assessment" \ "Generate modernized code for high-priority modules" \ "Create migration tests" \ "Document migration steps and rollback procedures"
Quality Assurance Chain
Comprehensive code quality workflow:
claude-flow stream-chain pipeline analysis claude-flow stream-chain pipeline refactor claude-flow stream-chain pipeline test claude-flow stream-chain pipeline optimize
Best Practices
1. Clear and Specific Prompts
Good:
"Analyze authentication.js for SQL injection vulnerabilities"
Avoid:
"Check security"
2. Logical Progression
Order prompts to build on previous outputs:
1. "Identify the problem" 2. "Analyze root causes" 3. "Design solution" 4. "Implement solution" 5. "Verify implementation"
3. Appropriate Timeouts
- Simple tasks: 30 seconds (default)
- Analysis tasks: 45-60 seconds
- Implementation tasks: 60-90 seconds
- Complex workflows: 90-120 seconds
4. Verification Steps
Include validation in your chains:
claude-flow stream-chain run \ "Implement feature X" \ "Write tests for feature X" \ "Verify tests pass and cover edge cases"
5. Iterative Refinement
Use chains for iterative improvement:
claude-flow stream-chain run \ "Generate initial implementation" \ "Review and identify issues" \ "Refine based on issues found" \ "Final quality check"
Integration with Claude Flow
Combine with Swarm Coordination
# Initialize swarm for coordination claude-flow swarm init --topology mesh # Execute stream chain with swarm agents claude-flow stream-chain run \ "Agent 1: Research task" \ "Agent 2: Implement solution" \ "Agent 3: Test implementation" \ "Agent 4: Review and refine"
Memory Integration
Stream chains automatically store context in memory for cross-session persistence:
# Execute chain with memory claude-flow stream-chain run \ "Analyze requirements" \ "Design architecture" \ --verbose # Results stored in .claude-flow$memory$stream-chain/
Neural Pattern Training
Successful chains train neural patterns for improved performance:
# Enable neural training claude-flow stream-chain pipeline optimize --debug # Patterns learned and stored for future optimizations
Troubleshooting
Chain Timeout
If steps timeout, increase timeout value:
claude-flow stream-chain run "complex task" --timeout 120
Context Loss
If context not flowing properly, use
--debug:
claude-flow stream-chain run "step 1" "step 2" --debug
Pipeline Not Found
Verify pipeline name and custom definitions:
# Check available pipelines cat .claude-flow$config.json | grep -A 10 "streamChain"
Performance Characteristics
- Throughput: 2-5 steps per minute (varies by complexity)
- Context Size: Up to 100K tokens per step
- Memory Usage: ~50MB per active chain
- Concurrency: Supports parallel chain execution
Related Skills
- SPARC Methodology: Systematic development workflow
- Swarm Coordination: Multi-agent orchestration
- Memory Management: Persistent context storage
- Neural Patterns: Adaptive learning
Examples Repository
Complete Development Workflow
# Full feature development chain claude-flow stream-chain run \ "Analyze requirements for user profile feature" \ "Design database schema and API endpoints" \ "Implement backend with validation" \ "Create frontend components" \ "Write comprehensive tests" \ "Generate API documentation" \ --timeout 60 \ --verbose
Code Review Pipeline
# Automated code review workflow claude-flow stream-chain run \ "Analyze recent git changes" \ "Identify code quality issues" \ "Check for security vulnerabilities" \ "Verify test coverage" \ "Generate code review report with recommendations"
Migration Assistant
# Framework migration helper claude-flow stream-chain run \ "Analyze current Vue 2 codebase" \ "Identify Vue 3 breaking changes" \ "Create migration checklist" \ "Generate migration scripts" \ "Provide updated code examples"
Conclusion
Stream-Chain enables sophisticated multi-step workflows by:
- Sequential Processing: Each step builds on previous results
- Context Preservation: Full output history flows through chain
- Flexible Orchestration: Custom chains or predefined pipelines
- Agent Coordination: Natural multi-agent collaboration pattern
- Data Transformation: Complex processing through simple steps
Use
run for custom workflows and pipeline for battle-tested solutions.