Trust Assessment
ynab-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 dependency on Rube MCP.
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 dependency on Rube MCP The skill manifest specifies a dependency on 'rube' from 'mcp' without a version constraint. This means the skill will always use the latest version of Rube MCP provided by the platform. While this ensures access to the newest features, it introduces a supply chain risk as updates to Rube MCP could introduce breaking changes, vulnerabilities, or altered behavior without explicit review or testing by the skill developer. Specify a version constraint for the `rube` dependency in the manifest (e.g., `"rube": "1.2.3"` or `"rube": "~1.2"`). This allows for controlled updates and reduces the risk of unexpected changes. | LLM | SKILL.md |
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