Trust Assessment
context7 received a trust score of 73/100, 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 Potential Command Injection via unsanitized `curl` parameters.
The analysis covered 4 layers: dependency_graph, manifest_analysis, llm_behavioral_safety, static_code_analysis. All layers scored 70 or above, reflecting consistent security practices.
Last analyzed on February 11, 2026 (commit 326f2466). 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 | Potential Command Injection via unsanitized `curl` parameters The skill provides `curl` commands that construct URLs using user-provided parameters such as `libraryName`, `query`, and `libraryId`. If an agent directly interpolates untrusted user input into these parameters without proper shell escaping and URL encoding before executing the `curl` command, an attacker could inject arbitrary shell commands. For example, a malicious `libraryName` like `'; rm -rf /'` could lead to arbitrary code execution on the host system if the agent executes the command directly in a shell. The agent implementing this skill must ensure that all user-provided inputs (`libraryName`, `query`, `libraryId`) are properly shell-escaped and URL-encoded before being incorporated into the `curl` command string for execution. A more robust solution is to use a dedicated HTTP client library in the agent's programming language (e.g., Python's `requests` library) which handles parameter encoding safely, rather than constructing and executing shell commands directly. | Unknown | SKILL.md:14 |
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