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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Trace2Skill: Distill Trajectory-Local Lessons into Transferable Agent Skills · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2603.25158/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2603.25158/feed.xml" rel="self" type="application/rss+xml" /><item><title>Trace2Skill: Distill Trajectory-Local Lessons into Transferable Agent Skills — mentioned by laxmena</title><link>https://news.ycombinator.com/item?id=48030777</link><guid isPermaLink="false">urn:hackerpapers:mention:2603.25158:48030777</guid><pubDate>Wed, 06 May 2026 00:48:56 GMT</pubDate><description>&lt;p&gt;That&amp;#x27;s exactly my process I follow now. I look at the traces of agent execution, and use that as a feedback to extract common patterns. The comment patterns are extracted out as Scripts, or Skills. So Agent doesnt have to figure out how to do things from scratch, saving considerable amount of tokens and latency. I also came across this paper recently: https://arxiv.org/abs/2603.25158 Which does exactly the same. Extracts traces and converts them into skills for agents to use.&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2603.25158/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.AI</category></item></channel></rss>
