Trust Assessment
tube-cog 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, 0 medium, and 1 low severity. Key findings include Unpinned Skill 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 20, 2026 (commit 89ffa28e). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| LOW | Unpinned Skill Dependency The skill manifest declares a dependency on 'cellcog' without specifying a version. This means that the latest available version of 'cellcog' will always be used, which could introduce breaking changes or vulnerabilities if a malicious or incompatible version is published in the future. While 'cellcog' appears to be another skill within the same ecosystem (installed via `clawhub`), unpinned dependencies generally increase supply chain risk. Specify a precise version or version range for the 'cellcog' dependency in the manifest to ensure consistent and secure behavior. For example: `"dependencies": ["cellcog==1.2.3"]` or `"dependencies": ["cellcog>=1.2.0,<2.0.0"]`. | Static | SKILL.md:1 |
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