Q&A Prep Partner

Predict challenging questions for presentations and prepare structured responses.

Usage

python scripts/main.py --abstract abstract.txt --field oncology
python scripts/main.py --topic "CRISPR therapy" --audience experts

Parameters

• --abstract: Abstract text or file
• --topic: Research topic
• --field: Research field
• --audience: Audience type (general/experts/peers)
• --n-questions: Number of questions to generate (default: 10)

Question Types

1. Methodology questions
2. Statistical questions
3. Interpretation questions
4. Limitation questions
5. Future work questions
6. Comparison questions

Output

• Predicted questions
• Suggested response frameworks
• Key points to address

Risk Assessment

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