Trust Assessment
gist-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 Broad Access to Gist Operations.
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 | Broad Access to Gist Operations The skill grants the AI agent broad access to 'Gist operations' via the Rube MCP. This includes the ability to create, read, update, and delete gists without explicit scope limitations defined within the skill itself. If the connected Gist account has access to sensitive or private gists, a compromised AI agent could potentially access or manipulate this data. The skill does not specify any read-only or limited scope permissions, implying full control over accessible gists. Consider if the AI agent truly requires full 'Gist operations' access. If possible, configure the underlying Gist connection or Rube toolkit to use the principle of least privilege, granting only necessary permissions (e.g., read-only access, access to specific public gists, or limited write capabilities). The skill description could also be updated to clarify any inherent scope limitations or recommended best practices for permission management. | LLM | SKILL.md:4 |
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