Meta-Analysis Forest Plotter

Create publication-quality forest plots for meta-analyses.

Use Cases

• Systematic review visualization
• Meta-analysis publication
• Evidence synthesis reporting

Parameters

Parameter	Type	Required	Default	Description
studies	str	Yes	-	Path to study data file with OR/RR and CI
effect_measure	str	No	"OR"	Effect measure: "OR", "RR", or "MD"
subgroup	str	No	-	Subgroup analysis variable (optional)

Returns

• Forest plot code (R meta package)
• Funnel plot for publication bias
• Heterogeneity statistics (I²)

Example

Input: 15 studies with OR and 95% CI Output: Publication-ready forest plot with pooled estimate

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

# Python dependencies
pip install -r requirements.txt

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