Two-phase pipeline for cleaning up speech recognition output: a dictionary that instantly fixes recurring errors you've seen before, then AI correction for everything else. The dictionary is basically a personalized cache that learns from your fixes, so it gets better over time at zero cost. Works best when you treat the first pass as a pre-filter and do the real work in the AI stage, especially on clean ASR where most errors are proper nouns the dictionary has never seen. The docs are unusually honest about when each phase actually helps. Includes a decision matrix for which corrections to save (non-words yes, common words no) and a triage system for the AI pass that separates confident fixes from things you need to verify from things you should leave alone. Built for transcripts from meetings, lectures, or interviews where you're fixing the same names and terms repeatedly.
npx skills add https://github.com/daymade/claude-code-skills --skill transcript-fixer