aipoch

dei-statement-drafter

Draft Diversity, Equity, and Inclusion statements for academic applications

aipoch 963 60 Updated 3mo ago

Resources

1
GitHub

Install

npx skillscat add aipoch/medical-research-skills/dei-statement-drafter

Install via the SkillsCat registry.

SKILL.md

DEI Statement Drafter

Draft Diversity, Equity, and Inclusion (DEI) statements for academic job applications and grant proposals.

Usage

python scripts/main.py --template faculty --experiences experiences.txt

Parameters

Parameter Type Default Required Description
--template, -t string faculty No Statement template (faculty, postdoc, grant)
--experiences, -e string - No File with DEI-related experiences
--output, -o string - No Output file path
--best-practices, -b flag - No Show DEI statement best practices

Statement Components

  • Personal background and perspective
  • DEI-related experiences
  • Future plans and commitment
  • Specific actions and initiatives

Output

  • Structured DEI statement
  • Section suggestions
  • Best practice tips

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