Security Audit
gmail-automation
github.com/sickn33/antigravity-awesome-skillsTrust Assessment
gmail-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 in manifest.
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 e36d6fd3). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| MEDIUM | Unpinned dependency in manifest The skill's manifest specifies a dependency on the 'rube' MCP without a version constraint. This means that updates to the 'rube' MCP could introduce breaking changes, vulnerabilities, or unexpected behavior without the skill author's explicit review, posing a supply chain risk. Specify a precise version or version range for the 'rube' MCP dependency in the manifest to ensure predictable behavior and mitigate supply chain risks. For example, `"mcp": ["rube@1.2.3"]` or `"mcp": ["rube@^1.0.0"]`. | LLM | SKILL.md:5 |
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