Trust Assessment
tushare received a trust score of 97/100, 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, 0 medium, and 1 low severity. Key findings include Unpinned Dependencies in Installation Instructions.
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
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| LOW | Unpinned Dependencies in Installation Instructions The skill's installation instructions recommend installing Python packages (`tushare`, `pandas`) without specifying exact versions. This can lead to supply chain risks if future versions of these packages introduce breaking changes, vulnerabilities, or malicious code. It's best practice to pin dependencies to specific versions to ensure reproducibility and security. Pin dependencies to specific versions in the installation instructions, e.g., `pip3 install tushare==X.Y.Z pandas==A.B.C --user`. Consider using a `requirements.txt` file for managing dependencies. | LLM | SKILL.md:28 |
Scan History
Embed Code
[](https://skillshield.io/report/9a3556960107920d)
Powered by SkillShield