Security Audit
Productboard Automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
Productboard 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
Behavioral Risk Signals
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| MEDIUM | Unpinned MCP dependency The skill's manifest specifies a dependency on the 'rube' Multi-Cloud Platform (MCP) without a version constraint. This means the skill will always use the latest version of the 'rube' MCP. While the URL `https://rube.app/mcp` is provided, relying on unversioned dependencies can introduce instability due to breaking changes or, in a worst-case scenario, compromise the skill if the 'rube' MCP were to be compromised with malicious updates. If the MCP system supports versioning for dependencies, specify a version constraint for the 'rube' MCP in the manifest (e.g., `"rube@1.0.0"`) to ensure consistent and secure behavior. Regularly review and update the pinned version. | Static | Manifest (frontmatter JSON) |
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