KOL Profiler
Key Opinion Leader analysis tool.
Use Cases
- KOL identification
- Collaboration mapping
- Speaker bureau selection
- Advisory board planning
Parameters
| Parameter | Type | Default | Required | Description |
|---|
| ----------- | ------ | --------- | ---------- | ------------- |
--therapeutic-area | string | - | Yes | Disease field or therapeutic area |
--geography | string | global | No | Regional scope (global, US, EU, Asia) |
--metrics | string | h-index | No | Metrics to analyze (h-index, citations, centrality, all) |
--output, -o | string | stdout | No | Output file path |
| --format | string | json | No | Output format (json, csv, html)
Returns
- Ranked KOL list
- Network visualization data
- Publication timeline
- Collaboration clusters
Example
Oncology KOLs in East Asia with high trial participation
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