KOL Profiler
name: kol-profiler
by aipoch-ai · published 2026-04-01
$ claw add gh:aipoch-ai/aipoch-ai-kol-profiler---
name: kol-profiler
description: Analyze physician academic influence and collaboration networks
version: 1.0.0
category: Pharma
tags: []
author: AIPOCH
license: MIT
status: Draft
risk_level: Medium
skill_type: Tool/Script
owner: AIPOCH
reviewer: ''
last_updated: '2026-02-06'
---
# KOL Profiler
Key Opinion Leader analysis tool.
Use Cases
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
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
Prerequisites
No additional Python packages required.
Evaluation Criteria
Success Metrics
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
- Performance optimization
- Additional feature support
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