Security Audit

clickmeeting-automation

github.com/ComposioHQ/awesome-claude-skills

AI SkillCommit 99e2a2951545

TRUSTED

Scanned about 2 months ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

clickmeeting-automation received a trust score of 86/100, 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, 1 high, 0 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

Manifest Analysis

100%

Static Code Analysis

100%

Dependency Graph

100%

LLM Behavioral Safety

85%

Security Findings1

Severity	Finding	Layer	Location
HIGH	Unpinned Rube MCP dependency The skill's manifest specifies a dependency on the 'rube' MCP without a pinned version. This introduces a supply chain risk, as updates to the 'rube' MCP could introduce breaking changes, vulnerabilities, or malicious code without explicit review. It is best practice to pin dependencies to specific versions or version ranges to ensure stability and security. Pin the 'rube' MCP dependency to a specific version or a narrow version range in the manifest's 'requires' section (e.g., `"rube": "^1.0.0"` or `"rube": "1.2.3"`).	LLM	SKILL.md:4

Scan History

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