Start by separating useful prose from chat scaffolding
Claude, Gemini, and ChatGPT can all help authors draft faster, but the output often arrives with chat scaffolding still attached. Prompts, role labels, alternative versions, assistant explanations, and setup notes can make a chapter feel like a transcript instead of a manuscript.
Before line editing, move the text into a cleanup workflow that treats the AI chat as source material. The goal is to keep the usable prose and remove the residue that helped during generation but does not belong in the book.
Look for the repeated artifacts first
The fastest wins are usually repeated artifacts: User and Assistant labels, phrases like here is a revised version, Markdown heading marks, duplicate summaries, filler transitions, and extra blank lines between paragraphs.
Awtter lets authors run focused cleanup passes with preview modals, match case, whole word matching, and line capture so every proposed removal can be checked before the draft changes.
Do not ask another AI pass to solve every cleanup problem
A rewrite prompt may remove some visible clutter, but it can also change voice, facts, pacing, or chapter intent. For cleanup, predictable rules are often safer than asking for a fresh rewrite of the whole passage.
Use manual cleanup for mechanical residue, then revise the remaining prose as writing. That keeps authors in control of the manuscript instead of turning cleanup into another generation step.
Turn the clean draft into a manuscript project
Once the obvious chat residue is gone, split the draft into chapters, scenes, front matter, back matter, research, and notes. A Binder-style structure makes it easier to review order, track status, and choose what belongs in the final export.
That structure also creates a safer path to DOCX, PDF, EPUB, TXT, Markdown, and ZIP files because the export comes from one reviewed source instead of a stack of copied drafts.