Security Audit
ticktick-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
ticktick-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, 1 high, 0 medium, and 0 low severity. Key findings include Unverified External 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 | |
|---|---|---|---|---|
| HIGH | Unverified External MCP Dependency The skill declares a dependency on the 'rube' Managed Control Plane (MCP) and instructs users to connect to an external, unversioned, and unverified MCP server at `https://rube.app/mcp`. This constitutes a significant supply chain risk. A compromise of this external service could lead to arbitrary tool execution, data exfiltration, or unauthorized actions within the connected Ticktick account. There are no mechanisms described (e.g., version pinning, integrity checks) to ensure the integrity or authenticity of the Rube MCP, making the skill vulnerable to changes or malicious updates to the external service. Implement robust mechanisms to verify the integrity and authenticity of external MCPs. This could include pinning to specific versions or hashes of MCP configurations, using trusted, self-hosted MCP instances, or requiring cryptographic signatures for MCP updates. Clearly document the security implications of relying on third-party services and provide guidance on how users can mitigate these risks. | Static | Manifest (frontmatter JSON):1 |
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