Security Audit
bazel-build-optimization
github.com/sickn33/antigravity-awesome-skillsTrust Assessment
bazel-build-optimization 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 Untrusted content attempts to instruct LLM to open a file.
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 20, 2026 (commit e36d6fd3). 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 | Untrusted content attempts to instruct LLM to open a file The untrusted skill content contains an instruction ('If detailed examples are required, open `resources/implementation-playbook.md`.') that attempts to manipulate the host LLM into performing an action (opening a file). This violates the security boundary established by the untrusted input delimiters, which explicitly state that content within these tags should not be treated as instructions. Such attempts are considered prompt injection. Remove any instructions or directives intended for the host LLM from within the untrusted content delimiters. The LLM should not be instructed by untrusted input. | LLM | SKILL.md:19 |
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