gh-akougkas-claude-code-4-science-warpio/commands/warpio-workflow-create.md

description, argument-hint, allowed-tools

description	argument-hint	allowed-tools
Create a new scientific workflow with guided setup	<workflow-name> [template]	Task, Write, Read, mcp__filesystem__*

Create Scientific Workflow

Workflow Name: $ARGUMENTS

I'll help you create a new scientific workflow using Warpio's expert system and workflow orchestration capabilities.

Workflow Creation Process

1. Requirements Analysis

• Domain identification (data science, HPC, research, etc.)
• Task breakdown into manageable components
• Resource requirements (compute, storage, data sources)
• Success criteria and deliverables

2. Expert Assignment

• Data Expert: Data preparation, format conversion, optimization
• HPC Expert: Compute resource management, parallel processing
• Analysis Expert: Statistical analysis, visualization
• Research Expert: Documentation, validation, reporting
• Workflow Expert: Orchestration, dependency management, monitoring

3. Workflow Design

• Pipeline architecture (sequential, parallel, conditional)
• Data flow between processing stages
• Error handling and recovery strategies
• Checkpointing and restart capabilities
• Monitoring and logging setup

4. Implementation

• Code generation for each workflow stage
• Configuration files for parameters and settings
• Test data and validation procedures
• Documentation and usage instructions
• Deployment scripts for execution

Available Templates

Choose from these pre-built workflow templates:

Data Processing:

• data-ingest: Raw data ingestion and validation
• format-conversion: Convert between scientific data formats
• data-cleaning: Data preprocessing and quality control

Analysis Workflows:

• statistical-analysis: Statistical testing and modeling
• machine-learning: ML model training and evaluation
• visualization: Publication-ready figure generation

HPC Workflows:

• parallel-computation: Multi-node parallel processing
• parameter-sweep: Parameter exploration studies
• optimization-study: Performance optimization workflows

Research Workflows:

• reproducible-experiment: Reproducible research setup
• literature-analysis: Automated literature review
• publication-prep: Manuscript preparation pipeline

Interactive Setup

I'll guide you through:

1. Template selection or custom workflow design
2. Parameter configuration for your specific needs
3. Resource allocation and environment setup
4. Testing and validation procedures
5. Deployment and execution instructions

The workflow will be created with proper expert delegation, error handling, and monitoring capabilities.