Comparison Table Gen

Auto-generates comparison tables for concepts, drugs, or study results in Markdown format.

Generates comparison tables for medical content.

Features

• Side-by-side comparisons
• Markdown table output
• Drug comparison templates
• Study result comparisons

Parameters

Parameter	Type	Default	Required	Description
--items, -i	string	-	Yes	Items to compare (comma-separated)
--attributes, -a	string	-	Yes	Comparison attributes (comma-separated)
--output, -o	string	-	No	Output JSON file path

Usage

bash

# Compare two drugs
python scripts/main.py --items "Drug A,Drug B" --attributes "Mechanism,Dose,Side Effects"

# Save to file
python scripts/main.py --items "Surgery,Chemo,Radiation" --attributes "Cost,Efficacy" --output comparison.json

Input Format

• items: Comma-separated list of items to compare (e.g., "Drug A,Drug B")
• attributes: Comma-separated list of comparison attributes (e.g., "Mechanism,Dose")

Output Format

json

{
  "markdown_table": "string",
  "html_table": "string"
}

Risk Assessment

Risk Indicator	Assessment	Level
Code Execution	Python/R scripts executed locally	Medium
Network Access	No external API calls	Low
File System Access	Read input files, write output files	Medium
Instruction Tampering	Standard prompt guidelines	Low
Data Exposure	Output files saved to workspace	Low

Security Checklist

• No hardcoded credentials or API keys
• No unauthorized file system access (../)
• Output does not expose sensitive information
• Prompt injection protections in place
• Input file paths validated (no ../ traversal)
• Output directory restricted to workspace
• Script execution in sandboxed environment
• Error messages sanitized (no stack traces exposed)
• Dependencies audited

Prerequisites

No additional Python packages required.

Evaluation Criteria

Success Metrics

• Successfully executes main functionality
• Output meets quality standards
• Handles edge cases gracefully
• Performance is acceptable

Test Cases

1. Basic Functionality: Standard input → Expected output
2. Edge Case: Invalid input → Graceful error handling
3. Performance: Large dataset → Acceptable processing time

Lifecycle Status

• Current Stage: Draft
• Next Review Date: 2026-03-06
• Known Issues: None
• Planned Improvements:
  • Performance optimization
  • Additional feature support