Security Audit
atlassian-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
atlassian-automation 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, 1 medium, and 0 low severity. Key findings include Reliance on external Rube MCP introduces supply chain risk.
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 27904475). 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 | Reliance on external Rube MCP introduces supply chain risk The skill's core functionality is entirely dependent on the external Rube MCP platform, specified by the endpoint `https://rube.app/mcp`. The security and integrity of this skill are directly tied to the trustworthiness and security practices of the Rube MCP service. Any compromise, malicious change, or availability issue within the Rube MCP platform could directly impact the operations performed by this skill, representing a significant supply chain risk. Evaluate the security posture and trustworthiness of the Rube MCP platform. Implement robust monitoring for the availability and behavior of the external service. Consider strategies for mitigating risks associated with third-party dependencies, such as version pinning if available, or alternative solutions if the risk is deemed too high. | LLM | SKILL.md:10 |
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