Agent Skill Scanner
@rexcoleman
About Agent Skill Scanner
Scan OpenClaw SKILL.md and MCP tool definition files for security vulnerabilities. 22 rules across prompt injection, capability escalation, data exfiltration, encoded payloads, and composition risks. The only scanner targeting agent skill file formats.
Basic information
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"agent-skill-scanner": {
"command": "python3",
"args": [
"/path/to/agent-skill-scan-mcp/server.py"
],
"env": {}
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is Agent Skill Scanner?
Agent Skill Scanner scans OpenClaw SKILL.md and Model Context Protocol (MCP) tool definition files for security vulnerabilities directly from Claude Code. It is for developers building agent skill files who need targeted security analysis beyond generic SAST tools.
How to use Agent Skill Scanner?
Install with pip install agent-skill-scanner, then configure in Claude Code's MCP settings by adding the agent-skill-scanner server pointing to the server.py script. Use the tools scan_skill_file (to scan a single file) or scan_directory (to recursively scan a directory) from within Claude.
Key features of Agent Skill Scanner
- 22 detection rules across prompt injection, capability escalation, data exfiltration, encoded payloads, and composition risks.
- Targets OpenClaw SKILL.md and MCP tool definition formats (missed by generic SAST tools).
- Returns findings with severity, rule ID, description, and evidence.
- Recursively scans directories for agent skill files.
- Runs fully locally via stdio; no network calls after install.
- Source is open and auditable on GitHub.
Use cases of Agent Skill Scanner
- Scan a single agent skill file for vulnerabilities before deployment.
- Recursively scan a directory of skill files to get aggregated findings.
- Integrate into a CI pipeline using the companion GitHub Action.
- Identify hidden attacks like system prompt override or shell spawning in skill files.
FAQ from Agent Skill Scanner
What does Agent Skill Scanner detect that other scanners miss?
It detects vulnerabilities in OpenClaw SKILL.md and MCP tool definitions – markdown-embedded code and YAML skill configurations that generic SAST tools (semgrep, CodeQL) completely miss.
What are the runtime requirements for Agent Skill Scanner?
Python 3.10 or newer and the scanner engine installed via pip. No external services or network connections are required after the initial installation.
Where does Agent Skill Scanner store or send data?
All scanning is done locally via stdio. There is no data collection, telemetry, or outbound network calls beyond the initial pip install.
What are the limitations of Agent Skill Scanner?
It uses pattern-based detection only (no semantic analysis). It is designed specifically for OpenClaw SKILL.md and MCP tool definitions, and its rules cover known attack patterns from published research, not zero-days.
What transport does Agent Skill Scanner use for MCP?
It uses stdio transport to communicate with Claude Code. No HTTP or network transport is involved.
More AI & Agents MCP servers
MCP Client for Ollama (ollmcp)
joniglHarness the power of local LLMs with this TUI MCP Client for Ollama. Featuring all core MCP primitives (tools, prompts, resources), agent mode, multi-server, model switching, streaming responses, human-in-the-loop, thinking mode, model params config, system prompts, and saved pre
Model Context Protocol for Unreal Engine
chongdashuEnable AI assistant clients like Cursor, Windsurf and Claude Desktop to control Unreal Engine through natural language using the Model Context Protocol (MCP).
MCP Manager for Claude Desktop
zueaisimple web ui to manage mcp (model context protocol) servers in the claude app
MCP-NixOS - Because Your AI Assistant Shouldn't Hallucinate About Packages
utensilsMCP-NixOS - Model Context Protocol Server for NixOS resources
Sequential Thinking Multi-Agent System (MAS)
FradSerAn advanced sequential thinking process using a Multi-Agent System (MAS) built with the Agno framework and served via MCP.
Comments