Security Audit
linear-automation
github.com/sickn33/antigravity-awesome-skillsTrust Assessment
linear-automation received a trust score of 80/100, 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, 1 high, 1 medium, and 0 low severity. Key findings include Excessive Permissions via Generic GraphQL Tool, Unpinned Dependency in Manifest.
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 Findings2
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| HIGH | Excessive Permissions via Generic GraphQL Tool The skill exposes a `LINEAR_RUN_QUERY_OR_MUTATION` tool that allows executing arbitrary GraphQL queries and mutations against the Linear API. This grants the agent (and potentially a malicious actor via prompt injection) the ability to perform any operation or retrieve any data that the connected Linear account has access to, bypassing the more granular controls of other specific Linear tools. This significantly broadens the attack surface for data exfiltration or unauthorized modifications. Consider if a generic GraphQL execution tool is strictly necessary. If so, implement strict input validation and sanitization for the `query` and `variables` parameters to limit the scope of operations. Alternatively, provide more specific tools for common advanced queries instead of a fully generic one. Ensure the agent's permissions to Linear are minimized to the absolute necessary scope. | LLM | SKILL.md:118 | |
| MEDIUM | Unpinned Dependency in Manifest The skill's manifest specifies a dependency on `rube` without a version constraint (`"mcp": ["rube"]`). This allows any version of the `rube` package to be used, which could introduce breaking changes, vulnerabilities, or malicious code if a future version is compromised or if a typosquatting package is installed. Pin the `rube` dependency to a specific, known-good version (e.g., `"mcp": ["rube==1.2.3"]`) or at least a major/minor version range (e.g., `"mcp": ["rube~=1.2"]`) to prevent unexpected or malicious updates. | LLM | SKILL.md |
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