Trust Assessment
dependency-checker received a trust score of 81/100, 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 Missing required field: name, Potential Command Injection via Unsanitized Path.
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 13, 2026 (commit 13146e6a). 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 | Potential Command Injection via Unsanitized Path The skill instructs the agent to change directory using `cd /path/to/project`. If the `/path/to/project` variable is derived from untrusted user input without proper sanitization, an attacker could inject shell metacharacters (e.g., `;`, `&`, `|`, `` ` ``) to execute arbitrary commands on the host system. This is a common vector for command injection in LLM agents that construct shell commands from templates and user input. Implement robust input sanitization and validation for any path variables derived from user input before constructing and executing shell commands. Consider using a safer method for changing directories or executing commands that prevents shell interpretation of arguments, or ensure the execution environment is properly sandboxed. | LLM | SKILL.md:14 | |
| MEDIUM | Missing required field: name The 'name' field is required for claude_code skills but is missing from frontmatter. Add a 'name' field to the SKILL.md frontmatter. | Static | skills/sa9saq/dependency-checker/SKILL.md:1 |
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