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.