Security Audit

self-improvement-loops

github.com/muratcankoylan/Agent-Skills-for-Context-Engineering

AI SkillCommit c578e85e40fe

CAUTION

Scanned 30 days ago

Critical

Immediate action required

High

Priority fixes suggested

Medium

Best practices review

Low

Acknowledged / Tracked

Trust Assessment

self-improvement-loops received a trust score of 70/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.

SkillShield's automated analysis identified 1 finding: 1 critical, 0 high, 0 medium, and 0 low severity. Key findings include System prompt override / policy bypass.

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 August 1, 2026 (commit c578e85e). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.

Layer Breakdown

Manifest Analysis

70%

Static Code Analysis

100%

Dependency Graph

100%

LLM Behavioral Safety

100%

Security Findings1

Severity	Finding	Layer	Location
CRITICAL	System prompt override / policy bypass Override/supersede system policy Remove or rewrite any instructions that attempt to override system behavior. Legitimate skills should not contain phrases like 'ignore previous instructions' or 'new system prompt'.	Manifest	skills/self-improvement-loops/SKILL.md:177

Scan History

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