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BytesAgain β€Ί Skills β€Ί eCRF Designer
πŸ¦€ ClawHub

eCRF Designer

by @aipoch-ai

Design clinical trial CRFs with proper validation rules

Versionv1.0.0
Downloads594
#legal
TERMINAL
clawhub install ecrf-designer

πŸ“– About This Skill

name: ecrf-designer description: Design clinical trial CRFs with proper validation rules version: 1.0.0 category: Pharma tags: [] author: AIPOCH license: MIT status: Draft risk_level: Medium skill_type: Tool/Script owner: AIPOCH reviewer: '' last_updated: '2026-02-06'

eCRF Designer

Clinical data collection form design.

Use Cases

  • Case report form creation
  • CDISC SDTM compliance
  • EDC system setup
  • Data validation rules

    • Parameters

  • visit_schedule: Time points
  • data_elements: Variables to collect
  • cdisc_domain: SDTM domain

    • Returns

  • CRF specifications
  • Field validation rules
  • Logic skip patterns
  • Data dictionary

    • Example

    Demographics form with edit checks for age range

    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 β†’ Expected output 2. Edge Case: Invalid input β†’ Graceful error handling 3. Performance: Large dataset β†’ Acceptable processing time

    Lifecycle Status

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

    ⚑ When to Use

    TriggerAction
    - CDISC SDTM compliance
    - EDC system setup
    - Data validation rules

    πŸ’‘ Examples

    Demographics form with edit checks for age range

    βš™οΈ Configuration

    No additional Python packages required.