Skills › Productivity & Integrations › Personal productivity
date-calculator
Calculates gestational age and follow-up date windows.
The full skill
—
name: date-calculator
description: Calculates gestational age and follow-up date windows.
version: 1.0.0
category: Utility
tags:
– dates
– pregnancy
– follow-up
– calculator
author: AIPOCH
license: MIT
status: Draft
risk_level: Medium
skill_type: Tool/Script
owner: AIPOCH
reviewer: ''
last_updated: '2026-02-06'
—
# Date Calculator
Calculates medical date windows.
## Features
– Gestational age
– Follow-up windows
– Visit scheduling
– Date adjustments
## Parameters
| Parameter | Type | Default | Required | Description |
|———–|——|———|———-|————-|
| `–type`, `-t` | string | – | Yes | Calculation type (gestational or followup) |
| `–date`, `-d` | string | – | Yes | Date in YYYY-MM-DD format |
| `–weeks` | int | 4 | No | Number of weeks for follow-up |
| `–window-days` | int | 7 | No | Follow-up window size in days |
| `–output`, `-o` | string | – | No | Output JSON file path |
## Usage
“`bash
# Calculate gestational age
python scripts/main.py –type gestational –date 2024-01-15
# Calculate 4-week follow-up window
python scripts/main.py –type followup –date 2024-03-01
# Calculate custom follow-up (6 weeks)
python scripts/main.py –type followup –date 2024-03-01 –weeks 6
“`
## Output Format
**Gestational calculation:**
“`json
{
"lmp_date": "2024-01-15",
"gestational_age": "12 weeks 3 days",
"gestational_age_days": 87,
"estimated_delivery_date": "2024-10-21",
"calculation_date": "2024-04-12"
}
“`
**Follow-up calculation:**
“`json
{
"start_date": "2024-03-01",
"followup_weeks": 4,
"window_start": "2024-03-29",
"window_end": "2024-04-05",
"window_range": "2024-03-29 to 2024-04-05"
}
“`
## 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