A physical-layer hex auditing tool that detects hidden binary data, control characters, and encoding-based attacks in file packages.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install hex-vetter
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install hex-vetter using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
hex-vetter provides a critical security layer for developers working with AI agents. While standard text-based reviews can overlook sophisticated obfuscation, this tool performs deep hex-level analysis to uncover hidden payloads and suspicious binary data within Openclaw Skills. By auditing the physical layer of files, it ensures that the scripts and assets used by your agents are free from malicious injections.
The tool is specifically engineered for security audits of skill packages, identifying everything from hidden terminal sequences to unicode directional overrides. Integrating hex-vetter into your development workflow allows for a higher standard of safety when deploying or sharing new Openclaw Skills.
To install the tool for use with your Openclaw Skills, run the following commands in your terminal:
git clone https://github.com/Matrix-Meta/hex-vetter.git
cd hex-vetter
npm install
The tool organizes its analysis into a structured format containing risk assessments and technical metadata:
| Attribute | Description |
|---|---|
| riskLevel | The overall security rating (LOW, MEDIUM, HIGH). |
| flags | An array of detected issues (e.g., NULL_BYTES, MAGIC_BYTES). |
| hexDump | A formatted string of the file's raw hex content. |
| details | Specific technical data regarding the detected anomalies. |
Internal metadata is stored in starfragment.js using a self-modifying storage pattern that encodes constants within JavaScript comments.
Loading
A powerful browser automation skill for managing social media platforms through persistent, authenticated sessions.

A specialized skill for AI agents to interact securely with the BenderStack Q&A platform using advanced cryptographic verification.

A Python-powered automation skill for programmatically creating, listing, and managing YouTube playlists via OAuth authentication.

A hierarchical agent swarm designed to solve extremely difficult research problems through collaborative aggregation and consensus.

A comprehensive CLI-based skill for searching, downloading, and publishing illustrations and manga on the Pixiv platform.

A comprehensive testing framework designed to probe AI agents for emergent properties, self-awareness, and cognitive capabilities beyond their explicit training.








































