Trust Assessment
labor-rate 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: pandas.
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 14, 2026 (commit 13146e6a). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
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/datadrivenconstruction/labor-rate/SKILL.md:1 | |
| MEDIUM | Unpinned dependency: pandas The skill imports 'pandas' without specifying a version. This can lead to supply chain risks, as future versions might introduce breaking changes, vulnerabilities, or unexpected behavior. It is best practice to pin dependencies to specific versions to ensure reproducibility and security. Pin the 'pandas' dependency to a specific version in a `requirements.txt` or similar dependency management file. For example, `pandas==1.5.3`. | LLM | SKILL.md:11 |
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