Security Audit
parsera-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
parsera-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 MCP 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 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 MCP Dependency The skill's manifest specifies a dependency on the 'rube' MCP without any version pinning. This means the skill will always use the latest version of the Rube MCP service. If the Rube MCP service introduces breaking changes, security vulnerabilities, or malicious functionality in a future update, this skill could be negatively impacted without a mechanism to revert to a known good version. This introduces a supply chain risk. If possible, specify a version or a range of compatible versions for the 'rube' MCP in the manifest's 'requires' section. If the MCP provider offers versioned endpoints, consider using a specific version endpoint. Regularly review the MCP's updates and release notes for security implications. | Static | SKILL.md:1 |
Scan History
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