Giving the llm access to Ghidra so it can directly read and iterate through the Sudoku puzzle that is decompile binaries seems like a good one. Ghidra has a cli mode and various bindings so you can automate decompiling various binaries. For example right now if you want to isolate the physics step of Microsoft flight simulator 3.0 codex will hold your hand and walk you through (over the course of 3-4 hours, using the gui) finding the main loop and making educated guesses about which decompiled c functions in there are likely physics related, but it would be a lot easier to just give it the "Ghidra" skill and say, "isolate the physics engine and export it as a portable cargo package in rust". If you're an NSA analyst you can probably use it to disassemble and isolate interesting behavior of various binaries from state actors a lot faster.

I don't know about life-changing but to me there are two major benefits that get me really interested:

- Augmenting CLI with specific knowledge and processes: I love the ability to work on my files, but I can only call a smart generalist to do the work. With skills if I want, say, a design review, I can write the process, what I'm looking for, and design principles I want to highlight rather than the average of every blog post about UX. I created custom gems/projects before (with PDFs of all my notes), but I couldn't replicate that on CLIs.

- Great way to build your library of prompts and build on it: In my org everyone is experimenting with AI but it's hard to document and share good processes and tools. With this, the copywriters can work on a "tone of voice" skill, the UX writers can extend it with an "Interface microcopy" skill, and I can add both to my "design review" agent.

Small use case but I’m using skills for analysing and scoring content then producing charts. LLM does the scoring then calls a Python script bundled in the skill that makes a variety of PNG charts based on metrics passed in via command line arguments. Claude presents the generated files for download. The skill.md file explains how to run the analysis and how to call the script and with what options. That way, you can get very consistent charts because they’re generated programmatically, but you can use the LLM for what it’s good at.

The best examples I've seen are still the ones built into ChatGPT and Claude to improve their abilities to edit documents.

The Claude frontend-design skill seems pretty good too for getting better HTML+CSS: https://github.com/anthropics/skills/blob/main/skills/fronte...

I have made a skill that uses Playwright to control Chrome together with functionality to extract HTML, execute JS, click things and most importantly log full network requests. It's a blessing for reverse-engineering and making userscripts.