claude-code openclaw automation

Skills date-calculator

Name: date-calculator
Author: openclaw

Calculates gestational age and follow-up date windows.

install

source · Clone the upstream repo

git clone https://github.com/openclaw/skills

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/aipoch-ai/date-calculator" ~/.claude/skills/openclaw-skills-date-calculator && rm -rf "$T"

OpenClaw · Install into ~/.openclaw/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/openclaw/skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/aipoch-ai/date-calculator" ~/.openclaw/skills/openclaw-skills-date-calculator && rm -rf "$T"

manifest: skills/aipoch-ai/date-calculator/SKILL.md

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

# 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:

{
  "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:

{
  "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

Basic Functionality: Standard input → Expected output
Edge Case: Invalid input → Graceful error handling
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