<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>LLM Evaluation on Top AI Skills</title><link>https://topaiskills.com/tags/llm-evaluation/</link><description>Recent content in LLM Evaluation on Top AI Skills</description><generator>Hugo</generator><language>en</language><lastBuildDate>Mon, 13 Jul 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://topaiskills.com/tags/llm-evaluation/index.xml" rel="self" type="application/rss+xml"/><item><title>DeepEval: Evaluate LLM Outputs with Your AI Coding Agent</title><link>https://topaiskills.com/skills/coding/deepeval/</link><pubDate>Mon, 13 Jul 2026 00:00:00 +0000</pubDate><guid>https://topaiskills.com/skills/coding/deepeval/</guid><description>&lt;p&gt;If you build AI-powered features, you&amp;rsquo;ve felt the pain. You ship a prompt change, and suddenly the model starts hallucinating in production. Or you switch from GPT-4 to Claude, and the output format breaks silently. DeepEval solves this — it&amp;rsquo;s the testing framework for LLM outputs, now available as an AI agent skill.&lt;/p&gt;
&lt;h2 id="what-it-does"&gt;What It Does&lt;/h2&gt;
&lt;p&gt;DeepEval treats LLM evaluation like unit testing. Instead of manually eyeballing outputs, you write test cases and metrics — hallucination score, answer relevancy, faithfulness, toxicity, bias, and more. Your agent runs these against your model&amp;rsquo;s responses and tells you what broke and why.&lt;/p&gt;</description></item></channel></rss>