Transcribe Refiner - Caption Cleanup Engine

Transform raw auto-generated captions into clean, readable transcripts with zero content loss.

Core Purpose

Auto-generated captions (Zoom, YouTube, Teams, etc.) are messy: fragmented sentences, timestamps everywhere, speaker tags on every line, filler words, transcription errors. This skill reconstructs them into coherent, flowing text that can be consumed by humans or downstream skills (like lecture-alchemist).

Critical Rules

Zero Content Loss

Every substantive statement, technical term, concept, question, and answer from the raw captions MUST appear in the output. Only noise is removed, never content.

Remove: Timestamps, redundant speaker tags, filler words (um, uh, basically, right?, you know), technical interruptions ("can you hear me?", "let me share my screen"), duplicate sentences from reconnection.

Preserve: Every teaching point, code reference, question asked, answer given, tangent with value, name, URL, command, or technical term.

Smart Error Correction

Auto-captions make predictable errors. Fix them using domain context: