Security Audit

hamelsmu/evals-skills:skills/validate-evaluator

github.com/hamelsmu/evals-skills

AI SkillCommit febdb335bd65

TRUSTED

Scanned 11 days ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

hamelsmu/evals-skills:skills/validate-evaluator 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 third-party dependency in installation instructions.

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 March 20, 2026 (commit febdb335). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis

100%

Static Code Analysis

93%

Dependency Graph

100%

LLM Behavioral Safety

100%

Security Findings1

Severity	Finding	Layer	Location
MEDIUM	Unpinned third-party dependency in installation instructions The skill instructs users to install the `judgy` Python package without specifying a version. This can lead to supply chain risks, as future versions of the package might introduce breaking changes, vulnerabilities, or even malicious code. It is best practice to pin dependencies to specific versions (e.g., `judgy==X.Y.Z`) to ensure reproducibility and security. Specify a precise version for the `judgy` package in the installation instructions, for example, `pip install judgy==1.2.3`, after verifying a known-good version.	Static	SKILL.md:164

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