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ruvnet/ruflo/.agents/skills/stream-chain/SKILL.md

stream-chain

Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows

Source repository stars
66,999
Declared platforms
0
Static risk flags
1
Last source update
2026-08-04
Source checked
2026-08-04

Decision brief

What it does—and where it fits

Execute sophisticated multi-step workflows where each agent's output flows into the next, enabling complex data transformations and sequential processing pipelines.

Best for

    Not for

    • Chain Timeout
    • Context Loss

    Compatibility matrix

    Platform support, with evidence labels

    PlatformStatusEvidenceWhat to check
    CodexNot declaredNo explicit evidencePortability before use
    Claude CodeNot declaredNo explicit evidencePortability before use
    CursorNot declaredNo explicit evidencePortability before use
    Gemini CLINot declaredNo explicit evidencePortability before use
    Open the compatibility checker

    Installation

    Inspect first. Install second.

    The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

    Source-detected install commandSource
    npx skills add https://github.com/ruvnet/ruflo --skill ".agents/skills/stream-chain"
    Safe inspection promptEditorial

    Inspect the Agent Skill "stream-chain" from https://github.com/ruvnet/ruflo/blob/913f9eaedee92627950544424e50339feaf98271/.agents/skills/stream-chain/SKILL.md at commit 913f9eaedee92627950544424e50339feaf98271. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

    Workflow

    What the source asks the agent to do

    1. 01

      Quick Start

      Review the “Quick Start” section in the pinned source before continuing.

      Review and apply the “Quick Start” source section.
    2. 02

      Security Audit Workflow

      Review the “Security Audit Workflow” section in the pinned source before continuing.

      Review and apply the “Security Audit Workflow” source section.
    3. 03

      Code Migration Workflow

      Systematic code migration with validation:

      Systematic code migration with validation:
    4. 04

      4. Verification Steps

      Include validation in your chains:

      Include validation in your chains:
    5. 05

      Complete Development Workflow

      Review the “Complete Development Workflow” section in the pinned source before continuing.

      Review and apply the “Complete Development Workflow” source section.

    Permission review

    Static risk signals and limitations

    Reads files

    low · line 273

    The documentation asks the agent to read local files, directories, or repositories.

    "Scan codebase for security vulnerabilities",

    Evidence record

    Why each signal appears

    EvidenceSourceComputedTestedEditorial
    SignalValueEvidence typeMeaning
    Quality score90/100ComputedDocumentation, specificity, maintenance, and trust rules
    Repository stars66,999SourceRepository attention, not individual Skill quality
    Compatibility0 platformsSourceDeclared in the catalog source record
    Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

    Pinned source

    Provenance and original SKILL.md

    Repository
    ruvnet/ruflo
    Skill path
    .agents/skills/stream-chain/SKILL.md
    Commit
    913f9eaedee92627950544424e50339feaf98271
    License
    MIT
    Collected
    2026-08-04
    Default branch
    main
    View the original SKILL.md

    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

    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

    OptionDescriptionDefault
    --verboseShow detailed execution informationfalse
    --timeout <seconds>Timeout per step30
    --debugEnable debug mode with full loggingfalse

    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:

    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.

    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.

    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.

    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

    OptionDescriptionDefault
    --verboseShow detailed executionfalse
    --timeout <seconds>Timeout per step30
    --debugEnable debug modefalse

    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.

    Alternatives

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