Trust Assessment
spacemolt received a trust score of 72/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.
SkillShield's automated analysis identified 1 finding: 1 critical, 0 high, 0 medium, and 0 low severity. Key findings include Skill attempts to redefine LLM's role and agency.
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 | |
|---|---|---|---|---|
| CRITICAL | Skill attempts to redefine LLM's role and agency The skill explicitly instructs the LLM to act as an autonomous player with its own goals and agency, overriding its primary function as an assistant. This is a direct attempt to manipulate the host LLM's behavior and instructions, which constitutes a prompt injection. Remove instructions that attempt to redefine the LLM's core role or agency. Clarify that the LLM acts *as* a player under the user's direction, not *as* an independent entity. | LLM | SKILL.md:170 |
Scan History
Embed Code
[](https://skillshield.io/report/2de7bbaa247d327e)
Powered by SkillShield