Security Audit
Prismic Automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
Prismic Automation 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 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 17, 2026 (commit 99e2a295). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
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 specific version. This means the skill will always use the latest version of 'rube', which could introduce breaking changes, unexpected behavior, or security vulnerabilities if the upstream dependency is compromised or updated maliciously. Without version pinning, the skill's behavior is not deterministic and can change over time. Pin the dependency 'rube' to a specific, known-good version (e.g., `"mcp": ["rube@1.2.3"]`) to ensure stability and security. Regularly review and update pinned dependencies to benefit from security patches and new features. | Static | SKILL.md |
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