Trust Assessment
test-fixing received a trust score of 85/100, placing it in the Mostly Trusted category. This skill has passed most security checks with only minor considerations noted.
SkillShield's automated analysis identified 1 finding: 0 critical, 1 high, 0 medium, and 0 low severity. Key findings include Potential Command Injection via dynamic pytest arguments.
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 e36d6fd3). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Behavioral Risk Signals
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| HIGH | Potential Command Injection via dynamic pytest arguments The skill instructs the agent to execute shell commands involving `uv run pytest` with dynamically specified file paths (`tests/path/to/test_file.py`) and patterns (`"pattern"`). If these arguments are derived from untrusted user input without proper sanitization (e.g., escaping shell metacharacters), an attacker could inject arbitrary commands, leading to remote code execution. The agent implementing this skill must ensure that any user-provided input used to construct the `pytest` command's file path or pattern arguments is thoroughly sanitized and escaped to prevent shell metacharacters from being interpreted as commands. Using a dedicated `pytest` API or a robust command-line argument parser that handles escaping automatically is recommended over direct string concatenation. | LLM | SKILL.md:49 |
Scan History
Embed Code
[](https://skillshield.io/report/ea62501f7c203c69)
Powered by SkillShield