<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Skills on DataAgentX</title><link>https://e343c64b.dataagentx.pages.dev/en/tags/skills/</link><description>Recent content in Skills on DataAgentX</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Sun, 13 Sep 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://e343c64b.dataagentx.pages.dev/en/tags/skills/index.xml" rel="self" type="application/rss+xml"/><item><title>OpenAI Data Analytics Skills as Reviewable Work Protocols</title><link>https://e343c64b.dataagentx.pages.dev/en/tech/20260913-openai-data-analytics-skills/</link><pubDate>Sun, 13 Sep 2026 00:00:00 +0000</pubDate><guid>https://e343c64b.dataagentx.pages.dev/en/tech/20260913-openai-data-analytics-skills/</guid><description>&lt;p&gt;“Why did conversion fall?” A demo agent can quickly locate a table, write SQL, draw a line, and suggest several causes. Delivery exposes the harder questions: What is the denominator? Is the current period complete? Did channel mix change? Are the “causes” measured contributions or a plausible story?&lt;/p&gt;&#10;&lt;p&gt;The Data Analytics Skills are useful because they turn analytical responsibility, handoffs, and completion criteria into reusable work protocols—not because of one special prompt.&lt;/p&gt;</description></item></channel></rss>