Concept Explainer

SKILL.md

---
name: concept-explainer
description: Uses analogies to explain complex medical concepts in accessible terms.
version: 1.0.0
category: Info
tags:
- education
- analogies
- medical-concepts
- explanation
author: AIPOCH
license: MIT
status: Draft
risk_level: Medium
skill_type: Tool/Script
owner: AIPOCH
reviewer: ''
last_updated: '2026-02-06'
---

# Concept Explainer

Explains medical concepts using everyday analogies.

## Features

- Analogy generation
- Concept simplification
- Multiple explanation levels
- Visual description support

## Parameters

| Parameter | Type | Default | Required | Description |
|-----------|------|---------|----------|-------------|
| `--concept`, `-c` | string | - | Yes | Medical concept to explain |
| `--audience`, `-a` | string | patient | No | Target audience (child, patient, student) |
| `--list`, `-l` | flag | - | No | List all available concepts |
| `--output`, `-o` | string | - | No | Output JSON file path |

## Usage

```bash
# Explain thrombosis to a patient
python scripts/main.py --concept "thrombosis"

# Explain to a child
python scripts/main.py --concept "immune system" --audience child

# Explain to a medical student
python scripts/main.py --concept "antibiotic resistance" --audience student

# List all available concepts
python scripts/main.py --list
```

## Output Format

```json
{
  "explanation": "string",
  "analogy": "string",
  "key_points": ["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
1. **Basic Functionality**: Standard input → Expected output
2. **Edge Case**: Invalid input → Graceful error handling
3. **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