No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by whylabs · Agent Tool · ★ 994
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🔒 Is langkit safe to install? View the security audit →
LangKit LangKit is an open-source text metrics toolkit for monitoring language models. It offers an array of methods for extracting relevant signals from the input and/or output text, which are compatible with the open-source data logging library whylogs. 💡 Want to experience LangKit? Go to this notebook! Table of Contents 📖 Motivation Features Installation Usage Modules Motivation 🎯 Productionizing language models, including LLMs, comes with a range of risks due to the infinite amount of input combinations, which can elicit an infinite amount of outputs. The unstructured nature of text poses a challenge in the ML observability space - a challenge worth solving, since the lack of visibility on the model's behavior can have serious consequences. Features 🛠️ The out of the box metrics include: Text Quality readability score complexity and grade scores Text Relevance Similarity scores between prompt/responses Similarity scores against user-defined themes [Security and Privacy](https://github.com/whylabs/la
| Stars | 994 |
| Forks | 74 |
| Language | Jupyter Notebook |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 69.9399208754836/100 |
| Open Issues | 37 |
| Last Updated | 2024-11-22 |
| Created | 2023-04-26 |
| Est. Tokens | ~351k |
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langkit 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 m. It is categorized as a Agent Tool with 994 GitHub stars.
langkit is primarily written in Jupyter Notebook. It covers topics such as large-language-models, machine-learning, nlg.
You can find installation instructions and usage details in the langkit GitHub repository at github.com/whylabs/langkit. The project has 994 stars and 74 forks, indicating an active community.
langkit is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to langkit on Agent Skills Hub include spacy-llm, free-ai-resources-x, prompttools. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
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