Skills dei-statement-drafter
Draft Diversity, Equity, and Inclusion statements for academic applications
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 "$T/skills/aipoch-ai/dei-statement-drafter" ~/.claude/skills/openclaw-skills-dei-statement-drafter && rm -rf "$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 "$T/skills/aipoch-ai/dei-statement-drafter" ~/.openclaw/skills/openclaw-skills-dei-statement-drafter && rm -rf "$T"
manifest:
skills/aipoch-ai/dei-statement-drafter/SKILL.mdsource content
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 |
|---|---|---|---|---|
| string | faculty | No | Statement template (faculty, postdoc, grant) |
| string | - | No | File with DEI-related experiences |
| string | - | No | Output file path |
| 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
- 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