Pattern: Token Cost Has Become Its Own Tooling Category

GitHub·medium signal

Token reduction has matured from a prompt-writing habit into a stack of dedicated, composable tools: transparent proxies (rtk, Headroom's headroomlabs-ai/headroom at 60–95% compression), output-compression skills (Caveman), and context-intelligence layers (yvgude/lean-ctx, thedotmack/claude-mem). Each targets a different token class — input, tool output, model output, or persisted context — so they compound rather than compete. Expect 'what's your token stack?' to become as routine a question as 'what's your model?'