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

<

prompt

1

>

<

prompt

2

>

[

..

.

]

[

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

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

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