Security Audit
precoro-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
precoro-automation received a trust score of 92/100, placing it in the Trusted category. This skill has passed all critical security checks and demonstrates strong security practices.
SkillShield's automated analysis identified 2 findings: 0 critical, 0 high, 1 medium, and 1 low severity. Key findings include Potential for excessive permissions via RUBE_REMOTE_WORKBENCH, Unpinned Rube MCP dependency in manifest.
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 Findings2
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| MEDIUM | Potential for excessive permissions via RUBE_REMOTE_WORKBENCH The skill recommends using `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()` for 'Bulk ops'. The term 'workbench' and the function `run_composio_tool()` suggest a more programmatic and potentially less constrained execution environment compared to direct tool invocations. Without clear details on the sandboxing, input validation, and scope of execution within `RUBE_REMOTE_WORKBENCH`, there is a risk that this tool could be used to perform actions with excessive permissions or execute arbitrary code beyond the intended scope of Precoro automation. Clarify the security model, sandboxing, and input validation mechanisms for `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`. Ensure that the execution environment is strictly isolated and that only authorized and validated operations can be performed, preventing arbitrary code execution or access to unintended resources. If possible, prefer more granular and constrained tool calls over a general 'workbench' for sensitive operations. | LLM | SKILL.md:70 | |
| LOW | Unpinned Rube MCP dependency in manifest The skill manifest specifies a dependency on `mcp: ["rube"]` without a version constraint. This means the skill could be exposed to breaking changes or security vulnerabilities introduced in future, unverified versions of the Rube MCP. Unpinned dependencies can lead to unexpected behavior or security regressions if the upstream dependency changes in an incompatible or malicious way. Specify a version constraint for the `rube` MCP dependency (e.g., `mcp: ["rube@^1.0.0"]`) in the manifest. This ensures that the skill relies on a known and tested version of the Rube MCP, improving stability and reducing supply chain risks. | LLM | SKILL.md:1 |
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