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Install in OpenClaw
/install concept-explainer
Description
Uses analogies to explain complex medical concepts in accessible terms.
README (SKILL.md)
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
# 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
{
"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
- 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
Usage Guidance
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 path—prefer running without --output or use a sandboxed workspace. (3) Note the skill is not a substitute for professional medical advice; review outputs for accuracy before sharing with patients. (4) SKILL.md mentions visual support which is not implemented—if you need that, validate or extend the code. (5) If you want stronger safety, run the script in an isolated environment and consider adding path validation and stricter input checks.
Capability Analysis
Type: OpenClaw Skill
Name: concept-explainer
Version: 0.1.0
The skill bundle contains a potential path traversal vulnerability in `scripts/main.py`, as the `--output` argument is used directly in a file write operation without any path sanitization or validation. While the functionality is aligned with the stated purpose of explaining medical concepts, the `SKILL.md` file includes a security checklist claiming that path validation and workspace restrictions are in place, which is not reflected in the actual code implementation. This lack of sanitization allows for arbitrary file overwrites if the agent is misdirected.
Capability Assessment
Purpose & Capability
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.
Instruction Scope
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.
Install Mechanism
Instruction-only / script-only skill with no install spec and no external dependencies; nothing is downloaded or installed by the skill.
Credentials
No environment variables, credentials, or config paths are requested. The script operates solely on command-line arguments and an internal static data map.
Persistence & Privilege
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.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install concept-explainer - After installation, invoke the skill by name or use
/concept-explainer - Provide required inputs per the skill's parameter spec and get structured output
Version History
v0.1.0
- Initial release of Concept Explainer.
- Explains medical concepts using accessible analogies.
- Supports tailored explanations for different audiences: child, patient, student.
- Provides JSON output with explanation, analogy, and key points.
- Includes a feature to list all available concepts.
- Medium risk level with basic security and risk assessment in place.
Metadata
Frequently Asked Questions
What is Concept Explainer?
Uses analogies to explain complex medical concepts in accessible terms. It is an AI Agent Skill for Claude Code / OpenClaw, with 216 downloads so far.
How do I install Concept Explainer?
Run "/install concept-explainer" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Concept Explainer free?
Yes, Concept Explainer is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Concept Explainer support?
Concept Explainer is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Concept Explainer?
It is built and maintained by AIpoch (@aipoch-ai); the current version is v0.1.0.
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