Trust Assessment
l2s-automation received a trust score of 93/100, 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 Unpinned Rube 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 17, 2026 (commit 99e2a295). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| MEDIUM | Unpinned Rube MCP dependency The skill manifest declares a dependency on the `rube` MCP but does not specify a version. This means that any changes or vulnerabilities introduced in future versions of the `rube` MCP could automatically affect this skill without explicit review or update, posing a supply chain risk. It is best practice to pin dependencies to specific versions to ensure stability and security. Pin the `rube` MCP dependency to a specific, known-good version in the manifest to ensure stability and security. For example, `"mcp": ["rube@1.2.3"]` if versioning is supported. | Static | Manifest (frontmatter JSON) |
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