Claude Code works best when it is given a concrete task with clear boundaries. Instead of asking for a vague rewrite, name the file, the behavior, the bug, or the expected outcome. Smaller scopes produce cleaner patches and make it easier to review what changed.
Useful context includes the file names involved, the current behavior, the desired behavior, and any constraints you care about. That is usually enough to keep Claude Code on track. Too little context leads to guessing, but too much unfiltered context can make the response noisier than it needs to be.
If you want a clean coding workflow, ask for a short explanation, the specific files touched, and the key reason for each change. That makes the output easier to review, easier to paste into a ticket or PR description, and easier to hand off to someone else on the team.
Update only the files needed for this bug. Keep the patch focused, summarize the fix, and note any test impact.
Claude Code is also useful for summarizing diffs, cleaning up notes, drafting explanations, and turning technical output into documentation or review comments. That is where formatting cleanup can become relevant, because copied AI-generated notes often need to be simplified before they go into PRs, docs, or project trackers.
Cleanup is useful when Claude Code output is correct but overly structured for the place you want to use it. If you copy notes, explanations, or generated summaries into tickets, docs, or comments, line-break and formatting cleanup can make the result look more natural.
Give it a concrete goal, relevant files, and a clear definition of done so the output stays focused and easier to review.
Ask for focused changes, explicit file targets, and a short summary of what changed instead of broad open-ended output.
Cleanup matters when generated explanations, notes, or summaries are copied into docs, tickets, comments, or other places where extra formatting becomes distracting.