interview-mock-partner
Simulates behavioral interview questions for medical professionals.
52
1.58x
Quality
27%
Does it follow best practices?
Impact
98%
1.58xAverage score across 3 eval scenarios
Securityby
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./scientific-skills/Academic Writing/interview-mock-partner/SKILL.mdInterview Mock Partner
Simulates medical job interview scenarios.
Features
- Behavioral questions
- Response feedback
- Common scenarios
- Improvement tips
Parameters
| Parameter | Type | Default | Required | Description |
|---|---|---|---|---|
--position | string | - | Yes | Target position title |
--experience-level | string | entry | No | Experience level (entry, mid, senior) |
--specialty | string | - | No | Medical specialty area |
--questions | int | 5 | No | Number of questions to generate |
--output, -o | string | stdout | No | Output file path |
Output Format
{
"questions": ["string"],
"sample_answers": ["string"],
"tips": ["string"]
}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
- Repository
- aipoch/medical-research-skills
- Commit
4a48721
- Last updated
- Created
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.