Trust Assessment
moltlang-skill 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 installation instruction.
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 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/jasonlnheath/moltlang-skill/skill.md:1 | |
| MEDIUM | Unpinned dependency installation instruction The skill documentation recommends installing the `moltlang` package using `pip install moltlang` without specifying a version. This makes the installation vulnerable to supply chain attacks, where a malicious or vulnerable version of the package could be installed if the package maintainer's account is compromised or if a new malicious package takes over the name. It is best practice to pin dependencies to specific versions to ensure reproducibility and security. Specify a version for the `moltlang` package in the installation instructions, e.g., `pip install moltlang==X.Y.Z`, or use a `requirements.txt` file with pinned versions if this skill has Python dependencies. | LLM | skill.md:36 |
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