Yes, it's a mess, and there will be a lot of churn, you're not wrong, but there are foundational concepts underneath it all that you can learn and then it's easy to fit insert-new-feature into your mental model. (Or you can just ignore the new features, and roll your own tools. Some people here do that with a lot of success.)
The foundational mental model to get the hang of is really just:
* An LLM
* ...called in a loop
* ...maintaining a history of stuff it's done in the session (the "context")
* ...with access to tool calls to do things. Like, read files, write files, call bash, etc.
Some people call this "the agentic loop." Call it what you want, you can write it in 100 lines of Python. I encourage every programmer I talk to who is remotely curious about LLMs to try that. It is a lightbulb moment.
Once you've written your own basic agent, if a new tool comes along, you can easily demystify it by thinking about how you'd implement it yourself. For example, Claude Skills are really just:
1) Skills are just a bunch of files with instructions for the LLM in them.
2) Search for the available "skills" on startup and put all the short descriptions into the context so the LLM knows about them.
3) Also tell the LLM how to "use" a skill. Claude just uses the `bash` tool for that.
4) When Claude wants to use a skill, it uses the "call bash" tool to read in the skill files, then does the thing described in them.
and that's more or less it, glossing over a lot of things that are important but not foundational like ensuring granular tool permissions, etc.