Trust Assessment
expanso-secrets-scan 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 Missing required field: name, Unpinned dependency for expanso-edge.
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 | Missing required field: name The 'name' field is required for claude_code skills but is missing from frontmatter. Add a 'name' field to the SKILL.md frontmatter. | Static | skills/aronchick/expanso-secrets-scan/SKILL.md:1 | |
| MEDIUM | Unpinned dependency for expanso-edge The skill requires the `expanso-edge` binary, which is installed via `clawhub install expanso-edge`. This command does not specify a version, meaning it will always install the latest available version. This introduces a supply chain risk, as a future update to `expanso-edge` could introduce breaking changes, vulnerabilities, or even malicious code without explicit review. It also makes the skill's behavior non-deterministic across different installation times. Pin the `expanso-edge` dependency to a specific, known-good version. For example, if `clawhub` supports versioning, use `clawhub install expanso-edge@1.2.3`. Regularly review and update the pinned version to benefit from security patches and new features. | LLM | SKILL.md:9 |
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