Security Audit

sendgrid-automation

github.com/sickn33/antigravity-awesome-skills

AI SkillCommit e36d6fd3b3f6

TRUSTED

Scanned about 10 hours ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

sendgrid-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 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 e36d6fd3). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis

100%

Static Code Analysis

100%

Dependency Graph

100%

LLM Behavioral Safety

93%

Behavioral Risk Signals

Network Access

1 finding

Security Findings1

Severity	Finding	Layer	Location
MEDIUM	Unpinned MCP Dependency The skill manifest specifies a dependency on the 'rube' MCP without a version constraint. This can lead to unexpected behavior or security vulnerabilities if future versions of 'rube' introduce breaking changes or malicious code. It's a supply chain risk as the skill's operational environment relies on an unversioned external component. Pin the 'rube' MCP dependency to a specific version or version range in the skill manifest to ensure stability and security (e.g., `"mcp": ["rube@1.2.3"]` or `"mcp": ["rube@^1.0.0"]`).	LLM	SKILL.md:6

Scan History

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