Trust Assessment
context7 received a trust score of 85/100, placing it in the Mostly Trusted category. This skill has passed most security checks with only minor considerations noted.
SkillShield's automated analysis identified 1 finding: 0 critical, 1 high, 0 medium, and 0 low severity. Key findings include Potential Command Injection via Unsanitized User Input in Shell Commands.
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 June 1, 2026 (commit 9b0e00ad). SkillShield performs automated 4-layer security analysis on AI skills and MCP servers.
Layer Breakdown
Behavioral Risk Signals
Security Findings1
| Severity | Finding | Layer | Location | |
|---|---|---|---|---|
| HIGH | Potential Command Injection via Unsanitized User Input in Shell Commands The skill's documentation describes executing `curl` commands with user-controlled parameters (`libraryName`, `query`, `libraryId`) and piping output to `jq`. If the agent directly interpolates user input into these shell commands without proper sanitization or shell escaping, a malicious user could inject arbitrary shell commands. For example, if a user provides input like `libraryName=foo; rm -rf /`, and this is directly inserted into the `curl` command executed by the agent, it could lead to arbitrary code execution on the host system. The `SKILL.md` explicitly shows `curl` commands, implying shell execution. The agent's implementation of this skill must rigorously sanitize and shell-escape all user-provided input before constructing and executing shell commands. Prefer using `subprocess.run` with `shell=False` and passing arguments as a list, or using a dedicated HTTP client library (e.g., Python's `requests`) for making web requests, which inherently handles URL encoding and avoids shell execution. If shell execution is unavoidable, ensure all user-controlled parameters are properly escaped for the shell environment. | LLM | SKILL.md:16 |
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