Security Audit
writer-automation
github.com/ComposioHQ/awesome-claude-skillsTrust Assessment
writer-automation received a trust score of 94/100, placing it in the Trusted category. This skill has passed all critical security checks and demonstrates strong security practices.
SkillShield's automated analysis identified 1 finding: 0 critical, 0 high, 1 medium, and 0 low severity. Key findings include Dynamic Tool Discovery and Execution Grants Broad 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 17, 2026 (commit 99e2a295). 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 | Dynamic Tool Discovery and Execution Grants Broad Permissions The skill instructs the LLM to use `RUBE_SEARCH_TOOLS` to dynamically discover available tools and then `RUBE_MULTI_EXECUTE_TOOL` or `RUBE_REMOTE_WORKBENCH` to execute them. This pattern grants the LLM broad permissions to interact with any tool exposed by Rube MCP, potentially beyond the intended 'Writer operations'. Specifically, `RUBE_REMOTE_WORKBENCH` with `run_composio_tool()` suggests a very general capability to execute arbitrary Composio tools. This increases the attack surface if the LLM is compromised or if Rube MCP exposes unintended functionalities. Implement stricter controls on the types of tools `RUBE_SEARCH_TOOLS` can return or `RUBE_MULTI_EXECUTE_TOOL`/`RUBE_REMOTE_WORKBENCH` can execute. Consider whitelisting specific tool slugs or categories if the scope is meant to be limited to 'Writer operations' only. Ensure the Rube MCP environment itself is sandboxed and only exposes necessary tools. | LLM | SKILL.md:80 |
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