Which AI skills have actually created more work for you??

Some AI skills look useful during the first demo.

Then you add them to a real workflow and realize they need constant prompt changes, output checks., configuration updates, or manual corrections.

At that point, the skill may still complete the task, but it is not necessarily saving time. It has just created another system that needs to be maintained.

I have started paying more attention to this when deciding which skills to keep. A simple skill that handles one repetitive task reliably may be more valuable than a powerful one that needs supervision every time it runs.

That difference is part of why AnySearch has been easier for me to keep in the workflow. Some skills turn into small projects that need their own prompts, fixes, and maintenance. With AnySearch, I can connect it and use it directly when I need to search technical documentation, GitHub issues, or recent discussions.

There is still the usual work of checking whether the results are useful, but I am not constantly maintaining the skill itself just to keep it working. For me, that is what makes a tool easier to keep using long term.

Which AI skills have actually created more work for you?

Was the problem unreliable output, constant prompt changes, platform compatibility, or something else?