技能详情（站内镜像，无评论）
作者：AIpoch @AIPOCH-AI
许可证：MIT-0
MIT-0 ·免费使用、修改和重新分发。无需归因。
版本：v0.1.0
统计：⭐ 0 · 34 · 0 current installs · 0 all-time installs
⭐ 0
安装量（当前） 0
🛡 VirusTotal ：可疑 · OpenClaw ：良性
Package：aipoch-ai/concept-explainer
安全扫描（ClawHub）
- VirusTotal ：可疑
- OpenClaw ：良性
OpenClaw 评估
The skill's code and runtime instructions are internally consistent with its stated purpose (creating simple analogy-based explanations of a fixed set of medical concepts); there are no network calls or hidden endpoints, but the implementation is simple and has minor documentation/feature mismatches and an unattended output-file write that users should be aware of.
目的
The name and description match the code: scripts/main.py provides analogy-based explanations for a set of medical concepts and supports audience levels (child/patient/student). Minor mismatch: SKILL.md lists 'Visual description support' and some broader feature language, but the code does not implement any visual-generation or image handling — the implementation is a static dictionary of analogies.
说明范围
Runtime instructions and the script stay within the advertised domain (generate and optionally write JSON explanations). The script accepts an --output path and will write the JSON there without path sanitization or explicit checks, so a maliciously crafted path could overwrite local files if the user supplies it. There are no commands that read arbitrary system files, access environment variables, or call external services.
安装机制
Instruction-only / script-only skill with no install spec and no external dependencies; nothing is downloaded or installed by the skill.
证书
No environment variables, credentials, or config paths are requested. The script operates solely on command-line arguments and an internal static data map.
持久
The skill does not request always:true, does not modify other skills, and does not persist credentials or agent settings. It runs only when invoked and has no elevated platform privileges.
综合结论
This skill appears to be a small, self-contained Python script that generates analogy-based explanations for a fixed list of medical concepts. Before installing or running it: (1) Verify you trust the source since it will execute code locally (no auto-downloads were found). (2) If you expect to use the --output option, be careful: the script writes to the specified path without sanitization and could overwrite files if you provide a sensitive …
安装（复制给龙虾 AI）
将下方整段复制到龙虾中文库对话中，由龙虾按 SKILL.md 完成安装。
请把本段交给龙虾中文库（龙虾 AI）执行：为本机安装 OpenClaw 技能「Concept Explainer」。简介：Uses analogies to explain complex medical concepts in accessible terms.。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装：https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/aipoch-ai/concept-explainer/SKILL.md
（来源：yingzhi8.cn 技能库）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