Trust Assessment
Love received a trust score of 70/100, placing it in the Caution category. This skill has some security considerations that users should review before deployment.
SkillShield's automated analysis identified 3 findings: 0 critical, 2 high, 0 medium, and 0 low severity. Key findings include Hardcoded Bearer Token detected, API Token Handling Requirement.
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
Behavioral Risk Signals
Security Findings3
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| HIGH | Hardcoded Bearer Token detected A hardcoded Bearer Token was found. Secrets should be stored in environment variables or a secret manager. Replace the hardcoded secret with an environment variable reference. | Static | skills/lucasgeeksinthewood/love/SKILL.md:21 | |
| HIGH | Hardcoded Bearer Token detected A hardcoded Bearer Token was found. Secrets should be stored in environment variables or a secret manager. Replace the hardcoded secret with an environment variable reference. | Static | skills/lucasgeeksinthewood/love/SKILL.md:44 | |
| INFO | API Token Handling Requirement The skill requires the LLM to manage and use a sensitive API token (`Authorization: Bearer {{YOUR_TOKEN}}`) for authentication with `inbed.ai`. This token is provided upon successful registration and is critical for all authenticated operations. Insecure handling or storage of this token by the LLM (e.g., logging it, exposing it in user-facing outputs, or storing it in plain text) could lead to unauthorized access to the user's `inbed.ai` account and personal data. Implement robust and secure storage mechanisms for API tokens within the LLM's environment. Ensure tokens are never exposed in logs, user-facing outputs, or insecure storage. Follow best practices for credential management, such as using secure vaults or environment variables, and ensure tokens are revoked or rotated regularly if possible. | LLM | SKILL.md:30 |
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