Security Audit
magnetic-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
magnetic-automation received a trust score of 89/100, 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, 0 high, 2 medium, and 0 low severity. Key findings include Broad Tool Execution Permissions Granted to LLM, Unpinned Dependency on Rube MCP.
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 | Broad Tool Execution Permissions Granted to LLM The skill explicitly instructs the LLM to use `RUBE_MULTI_EXECUTE_TOOL` and `RUBE_REMOTE_WORKBENCH` for executing 'Magnetic operations'. These tools are generic execution mechanisms that allow the LLM to perform any action available through the underlying 'magnetic' toolkit via Composio. This grants the LLM broad, unconstrained access to all functionalities of the 'magnetic' toolkit, potentially including sensitive operations like data modification or deletion, without specific permission scoping within the skill definition itself. While this is the intended design for a general automation skill, it means the LLM can wield significant power within the 'magnetic' ecosystem. Consider if the LLM truly requires access to *all* operations within the 'magnetic' toolkit. If not, explore options for more granular permission scoping within the Rube MCP or Composio framework, or provide more specific instructions to the LLM to limit its use of these broad execution tools to only necessary actions. | LLM | SKILL.md:49 | |
| MEDIUM | Unpinned Dependency on Rube MCP The skill's manifest declares a dependency on the 'rube' MCP (`'requires': {'mcp': ['rube']}`) without specifying a version. This means the skill will always use the latest available version of the Rube MCP. Unpinned dependencies introduce supply chain risks, as updates to the 'rube' MCP could introduce breaking changes, new vulnerabilities, or unexpected behavior without explicit review or control by the skill developer. Pin the dependency on the 'rube' MCP to a specific, known-good version. This ensures stability and allows for controlled updates after security review. For example, `"mcp": ["rube@1.2.3"]` (if versioning is supported by the platform). | LLM | SKILL.md:4 |
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