I don't use them.

Everything is organised into repos, i select the directories with the context the agent needs for the task. If I want it to adjust something in my homelab, I drop it into the homelab repo. Stuff agents need to do commonly has shell scripts to speed it up.

I do however have some system prompts. I pick the prompt based on the goal, whether I want to implement something, or just web search, or just need a short one-off command to be done.

We keep the skills in a repo, where an agentic workflow runs biweekly to check if their content drifted compared to the docs and opens PRs if they did. The repo is also a Claude plugin. The biggest problem is keeping skills up to date across users, so I developed a small Go binary that takes care of that across harnesses.

If I have a session with something that I expect to do it again, I ask Claude to make a skill out of it and store at user level somewhere at ~./claude/skills I think, so next time I can do just "/xyreport from-to" for example and dont have worry about leaving out things from the prompt or to rediscover some gotchas the agent ran into.

I create and refine my own skills and commit them to my dotfiles repository.

I run AI on my server. All skills and relevant info is saved to a Wiki. Agent only has an instruction to check the wiki (MCP) at the beginning and get the necessary context.

For the my branch of the Norwegian Government we have a public skill registry and a tool to sync them locally according to what «profile» you select, https://ki-utvikling.nav.no/verktoy

Source at navikt/copilot

Disclaimer: I hand curate them in the end

I keep most of my sessions in Zed (you can import them there anyway). After some big feature I let a frontier agent go over these sessions and suggest improvements. Typically I use gemini for this because it's really good at pruning text. Claude/GPT really wants to append more text for some reason.

I end up with smaller skills but more "actioned" skills. They kind of force the agent to do things the way that works well.

I keep my skills in a Home Manager repo and install them into my .claude / .codex / whathaveyou directory through the home manager config. I'll know if they don't work because they are specific instructions on how to git commit, how to merge code, how to author text (without the typical AI tells), or API usage documentation for specific libraries, etc. If they didn't work the agent would do things incorrectly and I'd notice.

And sometimes it doesn't follow the instructions well. I have a skill for that too: it tells the agent, given what it knows about attention and LLM:s in general, to evaluate the instructions and the mistake the LLM made, try to diagnose why it didn't follow the instructions as expected, and come up with an improvement of the skill based on that diagnosis.

I am testing out Skillshare https://skillshare.runkids.cc and I am using skills.sh to find skills.

You can have your own skill repository with Skillshare and sync across agents (symlinks or copys).

I’ve tried to keep up with “best practices” around AI use, but things are improving so quickly that I’ve largely given up. The vanilla agents are just fine for my needs as they come.