gh-akougkas-claude-code-4-science-warpio/commands/warpio-help-experts.md

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Detailed help for Warpio expert management	Read

Warpio Expert Management Help

Expert System Overview

Warpio's expert system consists of 5 specialized AI agents, each with domain-specific knowledge and tools.

Available Experts

🗂️ Data Expert

Purpose: Scientific data format handling and I/O optimization

Capabilities:

• Format conversion (HDF5 ↔ Parquet, NetCDF ↔ Zarr)
• Data compression and optimization
• Chunking strategy optimization
• Memory-mapped I/O operations
• Streaming data processing

Tools: HDF5, ADIOS, Parquet, Zarr, Compression, Filesystem

Example Tasks:

• "Convert my HDF5 dataset to Parquet with gzip compression"
• "Optimize chunking strategy for 10GB dataset"
• "Validate data integrity after format conversion"

📊 Analysis Expert

Purpose: Statistical analysis and data visualization

Capabilities:

• Statistical testing and modeling
• Data exploration and summary statistics
• Publication-ready visualizations
• Time series analysis
• Correlation and regression analysis

Tools: Pandas, Plot, Statistics, Zen MCP

Example Tasks:

• "Generate statistical summary of my dataset"
• "Create publication-ready plots for my results"
• "Perform correlation analysis on multiple variables"

🖥️ HPC Expert

Purpose: High-performance computing and cluster management

Capabilities:

• SLURM job submission and monitoring
• Performance profiling and optimization
• Parallel algorithm implementation
• Resource allocation and scaling
• Cluster utilization analysis

Tools: SLURM, Darshan, Node Hardware, Zen MCP

Example Tasks:

• "Submit this MPI job to the cluster"
• "Profile my application's performance"
• "Optimize memory usage for large-scale simulation"

📚 Research Expert

Purpose: Scientific research workflows and documentation

Capabilities:

• Literature review and paper analysis
• Citation management and formatting
• Method documentation
• Reproducible environment setup
• Research workflow automation

Tools: ArXiv, Context7, Zen MCP

Example Tasks:

• "Find recent papers on machine learning optimization"
• "Generate citations for my research paper"
• "Document my experimental methodology"

🔗 Workflow Expert

Purpose: Pipeline orchestration and automation

Capabilities:

• Complex workflow design and execution
• Data pipeline optimization
• Resource management and scheduling
• Dependency tracking and resolution
• Workflow monitoring and debugging

Tools: Filesystem, Jarvis, SLURM, Zen MCP

Example Tasks:

• "Create a data processing pipeline for my experiment"
• "Automate my analysis workflow with error handling"
• "Set up a reproducible research environment"

How to Use Experts

1. List Available Experts

/warpio-expert-list

2. Check Expert Status

/warpio-expert-status

3. Delegate Tasks

/warpio-expert-delegate <expert> "<task description>"

4. Examples

# Data operations
/warpio-expert-delegate data "Convert HDF5 to Parquet format"
/warpio-expert-delegate data "Optimize dataset chunking for better I/O"

# Analysis tasks
/warpio-expert-delegate analysis "Generate statistical summary"
/warpio-expert-delegate analysis "Create correlation plots"

# HPC operations
/warpio-expert-delegate hpc "Submit SLURM job for simulation"
/warpio-expert-delegate hpc "Profile MPI application performance"

# Research tasks
/warpio-expert-delegate research "Find papers on optimization algorithms"
/warpio-expert-delegate research "Generate method documentation"

# Workflow tasks
/warpio-expert-delegate workflow "Create data processing pipeline"
/warpio-expert-delegate workflow "Automate analysis workflow"

Best Practices

Task Delegation

• Be Specific: Provide clear, detailed task descriptions
• Include Context: Mention file formats, data sizes, requirements
• Specify Output: Indicate desired output format or location

Expert Selection

• Data Expert: For any data format or I/O operations
• Analysis Expert: For statistics, visualization, data exploration
• HPC Expert: For cluster computing, performance optimization
• Research Expert: For literature, citations, documentation
• Workflow Expert: For automation, pipelines, complex multi-step tasks

Performance Tips

• Local AI Tasks: Use for quick analysis, format validation, documentation
• Complex Tasks: Use appropriate experts for domain-specific complex work
• Resource Management: Experts manage their own resources and tools

Troubleshooting

Expert Not Responding

• Check expert status with /warpio-expert-status
• Verify required tools are available
• Ensure task description is clear and complete

Task Failed

• Check error messages for specific issues
• Verify input data and file paths
• Ensure required dependencies are installed

Performance Issues

• Monitor resource usage with /warpio-expert-status
• Consider breaking large tasks into smaller ones
• Use appropriate expert for the task type