I've spent the last few months obsessed with AI coding agents. Not just using them. Building alongside them and optimizing them for my use-cases. I've designed and tested various skills for agents like Claude Code, VScode Copilot, Codex, and Cursor, and I've watched closely to see where they hold up and where they quietly fall apart.
And they do fall apart. Usually in the same way. The agent does great for three steps, then does something dumb on step four, it starts backtracking and analyzing went wrong, and by the time it figures out the issue, the conetxt window is almost full, leaving you with 3 what-have-I-done-so-far.md files instead of a task done.
After enough of those moments, I stopped trying to make the agent smarter. I changed how I think about skill design entirely. This blog is about that shift, and the patterns that came out of it.
The skill that taught me this
The example I keep coming back to is a skill I built called confluence-publisher. The origin is boring but honest: I didn't have corporate access to a Confluence MCP server, so my agent had no native way to publish pages. Instead of waiting on IT, I built the bridge myself: a skill that takes markdown and publishes it to Confluence.
