Skill: aipoch-ai/concept-explainer (version 0.1.0)

--- 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

path: references/guidelines.md
content: # Concept Explainer - References

## Educational Resources
- Medical education best practices
- Analogical reasoning in science
- Health literacy guidelines


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)