Trust Assessment
trails received a trust score of 94/100, 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, 1 medium, and 0 low severity. Key findings include Unpinned dependency versions 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
Behavioral Risk Signals
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| MEDIUM | Unpinned dependency versions in installation instructions The skill instructs the LLM to generate installation commands using the 'latest version' without pinning specific versions (e.g., `@0xtrails/trails` instead of `@0xtrails/trails@1.2.3`). This practice can introduce supply chain risks, as new versions might contain breaking changes, vulnerabilities, or even malicious code if the package registry or maintainer account is compromised. It's safer to pin to specific major or minor versions to ensure reproducible builds and mitigate risks. Instruct the LLM to generate installation commands with pinned versions (e.g., `@0xtrails/trails@^1.0.0` or `@0xtrails/trails@1.2.3`) to mitigate supply chain risks and ensure reproducible builds. Alternatively, recommend using a lock file (e.g., `package-lock.json`, `yarn.lock`, `pnpm-lock.yaml`) to manage dependencies. | LLM | SKILL.md:100 |
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