Security Audit
dialpad-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
dialpad-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 Skill enables broad tool execution via RUBE_REMOTE_WORKBENCH.
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 | Skill enables broad tool execution via RUBE_REMOTE_WORKBENCH The skill documentation explicitly mentions and provides guidance for using `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()`. This tool, by its nature, suggests the ability to execute arbitrary Composio tools, which could grant an AI agent overly broad access to various functionalities beyond the immediate scope of Dialpad, depending on the available Composio toolkits. While the skill focuses on Dialpad, the `RUBE_REMOTE_WORKBENCH` is a generic execution mechanism that could lead to excessive permissions if not properly constrained. If `RUBE_REMOTE_WORKBENCH` is not strictly necessary for Dialpad automation, consider removing its mention or providing more specific guidance on its constrained use. Ensure that the agent's environment and tool access are properly sandboxed and that `run_composio_tool()` is restricted to only necessary operations. | LLM | SKILL.md:66 |
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