cover-letter-drafter
Generates professional cover letters for journal submissions and job applications in medical and academic contexts.
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npx tessl i github:aipoch/medical-research-skills --skill cover-letter-drafterOverall
score
61%
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Cover Letter Drafter
Creates tailored cover letters for academic and medical positions.
Features
- Journal submission cover letters
- Job application cover letters
- Fellowship application letters
- Customizable templates
Parameters
| Parameter | Type | Default | Required | Description |
|---|---|---|---|---|
--purpose | string | job | No | Cover letter type (journal, job, fellowship) |
--recipient, -r | string | - | Yes | Target journal or institution |
--key-points, -k | string | - | Yes | Comma-separated key points to highlight |
--title | string | - | No | Manuscript title (for journal submissions) |
--significance | string | - | No | Significance statement (for journal submissions) |
--author, --applicant, -a | string | Applicant | No | Author or applicant name |
--position | string | - | No | Position title (for job applications) |
--fellowship | string | - | No | Fellowship name (for fellowship applications) |
--output, -o | string | - | No | Output JSON file path |
Usage
# Journal submission cover letter
python scripts/main.py --purpose journal --recipient "Nature Medicine" \
--key-points "Novel findings,Clinical relevance" \
--title "Study X" --significance "major advance" --author "Dr. Smith"
# Job application cover letter
python scripts/main.py --purpose job --recipient "Harvard Medical School" \
--key-points "10 years experience,Published 20 papers" \
--position "Assistant Professor" --applicant "Dr. Jones"
# Fellowship application
python scripts/main.py --purpose fellowship --recipient "NIH" \
--key-points "Research excellence,Leadership skills" \
--fellowship "K99" --applicant "Dr. Lee"Output Format
{
"cover_letter": "string",
"subject_line": "string",
"word_count": "int"
}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
- Last updated
- Created
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