stream-chain by ruvnet

---
name: stream-chain
description: Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows
version: 1.0.0
category: workflow
tags: [streaming, pipeline, chaining, multi-agent, workflow]
---

# 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:

1. **Custom Chains** (`run`): Execute custom prompt sequences with full control
2. **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

```bash
claude-flow stream-chain run \
  "Analyze codebase structure" \
  "Identify improvement areas" \
  "Generate action plan"
```

### Execute a Pipeline

```bash
claude-flow stream-chain pipeline analysis
```

---

## Custom Chains (`run`)

Execute custom stream chains with your own prompts for maximum flexibility.

### Syntax

```bash
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

```bash
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

```bash
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

```bash
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

```bash
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

```bash
claude-flow stream-chain pipeline <type> [options]
```

### Available Pipelines

#### 1. Analysis Pipeline

Comprehensive codebase analysis and improvement identification.

```bash
claude-flow stream-chain pipeline analysis
```

**Workflow Steps:**
1. **Structure Analysis**: Map directory structure and identify components
2. **Issue Detection**: Find potential improvements and problems
3. **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.

```bash
claude-flow stream-chain pipeline refactor
```

**Workflow Steps:**
1. **Candidate Identification**: Find code needing refactoring
2. **Prioritization**: Create ranked refactoring plan
3. **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.

```bash
claude-flow stream-chain pipeline test
```

**Workflow Steps:**
1. **Coverage Analysis**: Identify areas lacking tests
2. **Test Design**: Create test cases for critical functions
3. **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.

```bash
claude-flow stream-chain pipeline optimize
```

**Workflow Steps:**
1. **Profiling**: Identify performance bottlenecks
2. **Strategy**: Analyze and suggest optimization approaches
3. **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

```bash
claude-flow stream-chain pipeline analysis
```

#### Extended Refactoring

```bash
claude-flow stream-chain pipeline refactor --timeout 60 --verbose
```

#### Debug Test Generation

```bash
claude-flow stream-chain pipeline test --debug
```

#### Comprehensive Optimization

```bash
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

```json
{
  "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

```bash
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:

```bash
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:

```bash
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:

```bash
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:

```bash
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:**
```bash
"Analyze authentication.js for SQL injection vulnerabilities"
```

**Avoid:**
```bash
"Check security"
```

### 2. Logical Progression

Order prompts to build on previous outputs:
```bash
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:
```bash
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:
```bash
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

```bash
# 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:

```bash
# 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:

```bash
# 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:

```bash
claude-flow stream-chain run "complex task" --timeout 120
```

### Context Loss

If context not flowing properly, use `--debug`:

```bash
claude-flow stream-chain run "step 1" "step 2" --debug
```

### Pipeline Not Found

Verify pipeline name and custom definitions:

```bash
# 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

```bash
# 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

```bash
# 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

```bash
# 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.