clean-movie-subtitles

name	clean-movie-subtitles
description	Clean a movie-subtitle file (SRT or plain text) into readable prose saved to a ` clean` file. Use when the user hands you a subtitle/transcript file and wants the timestamps stripped, sentences on separate lines, punctuation fixed, censored words restored, and leading dialogue dashes removed.

Claude skill: Clean movie subtitles

Turn a raw movie-subtitle file into clean, readable text. Given a path to an .srt or plain-text subtitle file, produce a cleaned copy saved beside it with a clean suffix (/tmp/Backrooms 2026.txt -> /tmp/Backrooms 2026 clean.txt). The cleanup:

1. Removes time marks (SRT cue numbers + --> timestamp lines; stray timestamps in plain text).
2. Puts each sentence on its own line.
3. Corrects punctuation.
4. Restores censored coarse words (f*ck -> fuck, sh*t -> shit, ...).
5. Removes leading dialogue dashes (- You okay? -> You okay?).
6. Removes empty lines.

This skill is standalone — it does not touch Anki and shares none of the Anki skills' references or note logic. It lives in this project only because its cleaned sentences are a natural input to add-english-word-to-anki.

Input

A single path to a subtitle file, given as the skill argument — SRT (.srt) or plain text (which may or may not contain timestamps), e.g. /clean-movie-subtitles '/tmp/Backrooms 2026.txt'.

Mode

Optional --dry-run (in either order with the path): do everything except the final write — report the derived output path and a short preview instead of creating the file, e.g. /clean-movie-subtitles --dry-run '/tmp/Backrooms 2026.txt'.

Helper script

Delegate the deterministic stripping to the script — run it; never read its source (its contract is documented here):

• .claude/skills/clean-movie-subtitles/scripts/strip_subtitles.py — run python3 ".claude/skills/clean-movie-subtitles/scripts/strip_subtitles.py" "<input path>". Removes SRT cue indices + --> timestamp lines, standalone/leading timestamps in plain text, inline formatting tags (<i>, <b>, <font …>, {…}), and empty lines. It keeps sound cues ([music]) and speaker labels (JOHN:) — you remove the speaker labels below. Prints JSON {output_path, format, text, input_lines, output_lines} to stdout (exit 0); on an unreadable path it prints {"error": …} to stderr and exits 2. It writes no file — you write the final output.

Steps

1. Resolve the input path and whether --dry-run is present from the arguments.
2. Run python3 ".claude/skills/clean-movie-subtitles/scripts/strip_subtitles.py" "<input path>". If it exits non-zero, stop and show the user the reported error. Otherwise take text (the stripped dialogue), output_path, format, and the line counts from its JSON.
3. Produce the cleaned text from text — this is your linguistic pass, not the script's:
   • One sentence per line. Join subtitle wrapping (a sentence split across cue lines, trailing - hyphenation) and split at sentence boundaries so each line holds exactly one sentence.
   • Correct punctuation: capitalization, missing terminal marks, spacing, and stray dashes left over from wrapping.
   • Restore censored coarse words: f*ck/f**k/f--- -> fuck, sh*t -> shit, a*s/a$$ -> ass, etc. Restore the obvious intended word; don't invent new profanity.
   • Remove leading dialogue dashes (- , – , — at the start of a line) that mark a speaker turn — e.g. - You okay, Macer? -> You okay, Macer? — but first use the dash to recognize that the line begins a new speaker turn / new sentence, so it is not joined onto the previous line during reflow.
   • Remove speaker labels (JOHN:, NARRATOR (V.O.):, a leading - MARY: — the dash goes too, per the bullet above) but keep sound/scene cues ([music], (GUNSHOT)) on their own lines.
   • Otherwise do not add, drop, translate, or summarize content — this is repair/reformat only.
   • No empty lines in the output.
   • For a long file, process text in order in chunks and concatenate — do not skim or abridge. Then sanity-check the result isn't drastically shorter than the input (guard against dropped content); if it is, redo the missing part.
4. Write the cleaned text to output_path with the Write tool.