93
TRUSTED0
Critical
Immediate action required
0
High
Priority fixes suggested
1
Medium
Best practices review
0
Low
Acknowledged / Tracked
Trust Assessment
ml-engineer received a trust score of 93/100, placing it in the Trusted category. This skill has passed all critical security checks and demonstrates strong security practices.
SkillShield's automated analysis identified 1 finding: 0 critical, 0 high, 1 medium, and 0 low severity. Key findings include Missing required field: name.
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 15, 2026 (commit 1823c3f6). 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 | Missing required field: name The 'name' field is required for claude_code skills but is missing from frontmatter. Add a 'name' field to the SKILL.md frontmatter. | Static | plugins/specweave-ml/skills/ml-engineer/SKILL.md:1 |
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