Security Audit
maintainx-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
maintainx-automation received a trust score of 94/100, placing it in the Trusted category. This skill has passed all critical security checks and demonstrates strong security practices.
SkillShield's automated analysis identified 1 finding: 0 critical, 0 high, 1 medium, and 0 low severity. Key findings include External MCP dependency introduces supply chain risk.
The analysis covered 4 layers: Manifest Analysis, Static Code Analysis, Dependency Graph, LLM Behavioral Safety. All layers scored 70 or above, reflecting consistent security practices.
Last analyzed on February 17, 2026 (commit 99e2a295). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Behavioral Risk Signals
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| MEDIUM | External MCP dependency introduces supply chain risk The skill explicitly declares a dependency on the 'rube' MCP in its manifest (`requires: {"mcp": ["rube"]}`). This introduces a supply chain risk, as the security and integrity of the skill are reliant on the 'rube' MCP system. Any vulnerabilities, compromises, or malicious changes within the 'rube' MCP or its associated infrastructure (`https://rube.app/mcp`) could directly impact the security of this skill and its operations. Thoroughly vet the security posture, maintenance, and reputation of the 'rube' MCP provider (`rube.app`). Implement robust supply chain security practices, including regular dependency scanning, integrity checks, and monitoring for known vulnerabilities in external components. Consider the implications of relying on a third-party system for critical automation tasks. | LLM | SKILL.md:1 |
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