Security Audit

better-proposals-automation

github.com/ComposioHQ/awesome-claude-skills

AI SkillCommit 27904475d127

TRUSTED

Scanned about 2 months ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

better-proposals-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 27904475). 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%

Security Findings1

Severity	Finding	Layer	Location
MEDIUM	Unpinned Dependency in Manifest The skill's manifest specifies a dependency on 'rube' within the 'mcp' ecosystem without a version constraint. This means the skill will always use the latest available version of 'rube', which could introduce breaking changes, unexpected behavior, or, in a worst-case scenario, malicious code if the upstream dependency is compromised or updated with harmful intent. This lack of pinning makes the skill vulnerable to supply chain attacks or instability due to unannounced changes. Specify a version constraint for the 'rube' dependency in the manifest's 'requires' section (e.g., 'rube==1.0.0' or 'rube>=1.0.0,<2.0.0') to ensure stability and mitigate risks from unreviewed updates.	LLM	SKILL.md:4

Scan History

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