Trust Assessment
crypto-levels received a trust score of 93/100, placing it in the Trusted category. This skill has passed all critical security checks and demonstrates strong security practices.
SkillShield's automated analysis identified 2 findings: 0 critical, 0 high, 1 medium, and 0 low severity. Key findings include Suspicious import: requests, Unpinned Third-Party Dependency.
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/362224222/crypto-levels/scripts/analyze_levels.py:7 | |
| INFO | Unpinned Third-Party Dependency The 'requests' library is imported by 'analyze_levels.py' and 'test_analyzer.py'. Without a 'requirements.txt' or similar dependency management file specifying a pinned version, there's a risk that a future malicious or vulnerable version of 'requests' could be installed, leading to supply chain compromise. While 'requests' is a widely used library, best practice dictates pinning dependencies to known good versions. Add a 'requirements.txt' file to the skill package, specifying a pinned version for 'requests' (e.g., 'requests==2.28.1'). Ensure that the skill's deployment environment installs dependencies from this pinned file. | LLM | scripts/analyze_levels.py:10 |
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