Security Audit
gamma-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
gamma-automation received a trust score of 82/100, placing it in the Mostly Trusted category. This skill has passed most security checks with only minor considerations noted.
SkillShield's automated analysis identified 2 findings: 0 critical, 1 high, 1 medium, and 0 low severity. Key findings include Broad execution capabilities via RUBE_REMOTE_WORKBENCH, Unpinned Rube 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 20, 2026 (commit 27904475). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Behavioral Risk Signals
Security Findings2
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| HIGH | Broad execution capabilities via RUBE_REMOTE_WORKBENCH The skill exposes `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()` for 'Bulk ops'. This suggests a highly privileged execution environment that could allow the LLM to perform arbitrary operations or execute unconstrained code if the underlying `run_composio_tool()` is not properly sandboxed or restricted. This grants excessive permissions to the LLM and any user interacting with it, potentially leading to unauthorized actions or data manipulation. Clarify and restrict the capabilities of `RUBE_REMOTE_WORKBENCH` and `run_composio_tool()`. Ensure it operates within a strictly defined and sandboxed environment. Document the exact scope of operations allowed and implement robust access controls to prevent arbitrary code execution or unauthorized bulk operations. | LLM | SKILL.md:57 | |
| MEDIUM | Unpinned Rube MCP dependency The skill's manifest specifies a dependency on `mcp: ['rube']` without a version constraint. This means the skill will always use the latest version of Rube MCP, which could introduce breaking changes, vulnerabilities, or even malicious code if the `rube` MCP is compromised. This lack of pinning creates a supply chain risk, as updates to the dependency are automatically accepted without review. Specify a precise version or version range for the `rube` MCP dependency in the skill's manifest to ensure stability and mitigate supply chain risks. For example, `mcp: ['rube@1.2.3']` or `mcp: ['rube@^1.0.0']`. | LLM | SKILL.md:3 |
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