We are witnessing a resurgence and evolution of Command Line Interfaces (CLIs), accelerated by AI agents. Text-based, scriptable CLI tools work very well with LLM-based workflows. Accessing Wikipedia articles during an agent session is common. Usually, a webfetch call is used to get the HTML for a page from a URL like https://en.wikipedia.org/wiki/2026_Winter_Olympics. That works, and LLMs are smart enough to read HTML. But there is a cost: HTML is for rendering, so the model must ignore a lot of non-content markup to get to the useful text. i That increases token usage and adds context noise. Can we improve this?
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