Stream-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 (
run): Execute custom prompt sequences with full control
- Predefined Pipelines (
pipeline): Use battle-tested workflows for common tasks
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)
Execute 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 |
|---|
--verbose | Show detailed execution information | false |
--timeout <seconds> | Timeout per step | 30 |
--debug | Enable debug mode with full logging | false |
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)
Execute 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 |
|---|
--verbose | Show detailed execution | false |
--timeout <seconds> | Timeout per step | 30 |
--debug | Enable debug mode | false |
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.