Trust Assessment
google-search received a trust score of 87/100, 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 Suspicious import: requests, Unpinned Python Dependencies.
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 | |
|---|---|---|---|---|
| MEDIUM | Suspicious import: requests Import of 'requests' detected. This module provides network or low-level system access. Verify this import is necessary. Network and system modules in skill code may indicate data exfiltration. | Static | skills/mxfeinberg/google-search/scripts/search.py:3 | |
| MEDIUM | Unpinned Python Dependencies The `scripts/search.py` file uses the `requests` library but does not specify its version or pin its dependencies using a `requirements.txt` or similar mechanism. This can lead to supply chain vulnerabilities if a new version of `requests` or its transitive dependencies introduces a security flaw, or if a malicious package is published under the same name. Without pinned dependencies, the skill might inadvertently pull in vulnerable or malicious code. Add a `requirements.txt` file to the skill package, specifying exact versions for all direct and transitive dependencies (e.g., `requests==2.28.1`). Use a dependency management tool like `pip-tools` or `poetry` to manage and pin dependencies effectively. | LLM | scripts/search.py:4 |
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