Trust Assessment
clawdio received a trust score of 95/100, 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 external dependencies in recommended integration code.
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 external dependencies in recommended integration code The skill's integration examples recommend using external JavaScript libraries (`@coinbase/agentkit`, `@x402/fetch`) without specifying exact versions. This practice can introduce supply chain risks for the agent's implementation, as updates to these libraries could inadvertently introduce vulnerabilities, breaking changes, or malicious code without explicit developer review. While these are reputable libraries, pinning versions is a critical security best practice. Recommend specifying exact versions for all external dependencies in integration examples (e.g., `@coinbase/agentkit@1.2.3` and `@x402/fetch@1.0.0`). This ensures deterministic builds and reduces the risk of unexpected changes from upstream dependencies. | LLM | SKILL.md:169 |
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