Trying a new AI skill is easy. Deciding whether it deserves a permanent place in your workflow is much harder. I have started judging skills with a few simple questions: Does it solve a problem I face regularly? Does it work without constant prompt changes? Can I still use it if I switch models or agent platforms? Does it save more time than it takes to maintain? These questions have changed how I look at new tools. A great demo is no longer enough to convince me. I would rather keep a simple, reliable skill that helps me every day than a powerful one I only use once a month. Search, file handling, and automation skills seem more likely to stay because they support tasks I need repeatedly. I have also been reading discussions in r/AnySearchAI about search skills, context quality, and agent workflows. Instead of simply introducing tools, conversations based on real use cases have been much more helpful for deciding whether a skill is actually worth keeping long term. But I still have not found a clear standard. What makes an AI skill good enough to become a permanent part of your workflow? And what makes you eventually remove one? submitted by /u/Ijusdontgiveafuck
Originally posted by u/Ijusdontgiveafuck on r/ArtificialInteligence
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