Security Audit
precoro-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
precoro-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 Use of RUBE_REMOTE_WORKBENCH suggests excessive permissions.
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 | Use of RUBE_REMOTE_WORKBENCH suggests excessive permissions The skill recommends using `RUBE_REMOTE_WORKBENCH` for 'Bulk ops' with `run_composio_tool()`. The term 'workbench' and the generic nature of `run_composio_tool()` suggest that this tool might grant broad, potentially excessive, permissions to the AI agent. Depending on the implementation of `run_composio_tool()` and the available Composio tools, this could allow the agent to perform actions beyond the intended scope of Precoro automation, potentially leading to data manipulation, unauthorized access, or even command injection if `run_composio_tool()` allows arbitrary code execution. Clarify the exact capabilities and limitations of `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`. If it allows arbitrary code execution or access to sensitive system resources, ensure proper sandboxing and least privilege principles are applied. If its scope is intended to be limited to specific Composio tools, document these limitations clearly and consider if a more specific tool call would be appropriate instead of a generic 'workbench'. | LLM | SKILL.md:49 |
Scan History
Embed Code
[](https://skillshield.io/report/10222b276805ef0a)
Powered by SkillShield