I read this post thinking "Finally! Finally someone will explain to me what I've been missing because 'skills' just seem to be re-usable text that help make prompting faster."
Nope. Still the same.
Nope. Still the same.
Thank you! That made it clear to me why it's an useful caching technique.
So in essence, the ideal skill imo is pretty much a list of shell commands with a sentence next to each of when to use them
With these, I personally have skills for:
- dealing with our metrics and tracing platform
- dealing with jira
- dealing with confluence (mostly finding info I need via different search strategies without using too many tokens)
- dealing with database
- doing reviews (this one is more prompting about what info I need to review well myself, rather than commands, though it does instruct the agent to download the branch into a new worktree and clean it up after its done with specific commands)
Im generally suspicious of people with hundreds of skills, especially those I open and find ai generated writing inside. skills should be a list of commands, maybe with some pitfalls for the agent to avoid, added only by human experience (agents are terrible at prompting)
Tldr: you're doing it wrong but I will not show you how to do it right. I also did not run the bench using my approach but it definitely “vibes better” to me, and I reject your actual research paper.
Come on, show us some actual skills.
That one you use all the time looks a hell of a lot like “I wont a deterministic shell script for something a skill saying ‘run the shell script’”
Is that what you do? How much time do you spend on them? How do you stop the agent from making a bunch of very similar skills? How do you deal with the explosion of the total number of skills impacting your token use? Do you use skills from github, or is that bad practice? Why?
So many unanswered questions; so little content. :/