Security audit of whylabs/langkit · Agent Tool by whylabs · ★ 998
Yes — langkit passed AgentSkillsHub's rule-based security scan with no dangerous patterns detected. As with any third-party skill, confirm what credentials it requests before production use.
What it is: 🔍 LangKit: An open-source toolkit for monitoring Large Language Models (LLMs). 📚 Extracts signals from prompts & responses, ensuring safety & security. 🛡️ Features include text quality, relevance metrics, & sentiment analysis. 📊 A comprehensive tool for LLM observability. 👀
No dangerous patterns were detected: no credential exfiltration, no obfuscated downloads, no sandbox-escape attempts, no prompt-injection markers.
| Security grade | ✓ SAFE |
| Quality score | 70/100 |
| GitHub stars | 998 |
| Language | Jupyter Notebook |
| License | Apache-2.0 |
| Last updated |
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This is AgentSkillsHub's free basic audit: an automated rule-based scan with 42 published rules built on SlowMist's agent-security taxonomy (credential theft, obfuscated payloads, privilege escalation, covert instructions to the agent, and more) across 186,000+ open-source AI agent skills and MCP servers, refreshed every 8 hours. A SAFE grade is a scan result, not a guarantee — deep 5-dimension audits (code · credentials · vendor · supply-chain · operational) are available for enterprise. Audited: .