Security Audit
ritekit-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
ritekit-automation received a trust score of 85/100, placing it in the Mostly Trusted category. This skill has passed most security checks with only minor considerations noted.
SkillShield's automated analysis identified 1 finding: 0 critical, 0 high, 1 medium, and 0 low severity. Key findings include Unpinned external MCP dependency.
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 20, 2026 (commit 27904475). 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 | Unpinned external MCP dependency The skill relies on an external Managed Control Plane (MCP) at `https://rube.app/mcp`. There is no mechanism described to pin the version or verify the integrity of this external service. A compromise or malicious update to the 'rube' MCP could lead to unexpected behavior, security vulnerabilities, or data exfiltration without the skill's or user's knowledge, as the skill would automatically use the latest version served by the endpoint. Implement mechanisms to pin the version of the Rube MCP or verify its integrity (e.g., by hashing its served code/API definitions if possible) before use. Alternatively, consider hosting a trusted, version-controlled instance of the Rube MCP. | LLM | SKILL.md:30 |
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