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Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Capabilities

Features and capabilities supported by this server

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
healthcheck

Return server readiness.

count_signal_background

Extract signal and background event counts in defined kinematic regions.

    Args:
        mom_list: Reconstructed momentum values
        time_list: Reconstructed time values
        mc_list: MC truth labels
        mom_range: [min, max] momentum window for signal region
        time_range: [min, max] time window for signal region
        sign: Particle sign ("minus" for electrons, "plus" for positrons)
        
    Returns:
        Dictionary with signal count, background count, and event statistics
    
analyze_cuts

Initialize and configure analysis cuts for event selection.

    Args:
        cut_definitions: Dictionary defining cut criteria
        sign: Particle sign ("minus" or "plus")
        
    Returns:
        Dictionary with cut configuration and status
    
compute_sensitivity

Compute physics sensitivity metrics (significance, limits, intervals).

    Args:
        s_expected: Expected signal events
        b_expected: Expected background events
        b_sys_uncertainty: Systematic uncertainty on background
        exposure: Detector exposure (for normalization)
        efficiency: Signal detection efficiency
        
    Returns:
        Dictionary with significance, CLs limits, and Feldman-Cousins intervals
    
initialize_ml_selector

Initialize the machine learning selector for BDT-based event selection.

    Returns:
        Dictionary with initialization status and available features
    
get_cut_efficiency

Calculate efficiency metrics for applied cuts.

    Args:
        cuts_applied: Dictionary describing cuts applied
        n_total: Number of events before cuts
        n_surviving: Number of events after cuts
        
    Returns:
        Dictionary with efficiency and related metrics
    
summarize_analysisA

Generate a summary of analysis results for a dataset.

    Args:
        dataset_name: Name of the dataset analyzed
        sign: Particle sign
        n_events_processed: Total events processed
        signal_count: Reconstructed signal events
        background_count: Reconstructed background events
        ml_score_mean: Mean ML BDT score (if available)
        
    Returns:
        Dictionary with analysis summary
    
list_available_datasetsA

List available SAM dataset definitions for Mu2e analysis.

    Returns:
        Dictionary with available datasets and their descriptions
    
get_dataset_infoA

Get information about a specific SAM dataset definition.

    Args:
        defname: SAM definition name (e.g., 'ensembleMDS3c')
        location: File location ('disk', 'tape', 'scratch', 'nersc')
        
    Returns:
        Dictionary with dataset information: file count, size, availability
    
create_dataset_filelistA

Create a filelist for analysis from a SAM dataset definition.

    This tool prepares a dataset for use with refana analysis tools.
    
    Args:
        defname: SAM definition name (e.g., 'ensembleMDS3c')
        location: File location ('disk', 'tape', 'scratch', 'nersc')
        max_files: Limit to first N files (useful for testing)
        output_path: Path to save filelist (if None, generates temp path)
        
    Returns:
        Dictionary with filelist path and dataset information
    

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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