Yt Chapters

Generate accurate YouTube chapters from the final edited video at $ARGUMENTS.

Workflow Context

Final step of the weekly content pipeline — runs post-edit when the editor delivers the final .mp4. Do NOT run this before filming or editing. After this, the description is ready to copy-paste into YouTube.

Flow

Step 1: Parse Input

From $ARGUMENTS, extract:

• Video path: The local .mp4 file (required)
• Slug (optional): --slug <video-slug> to identify the video package at ~/content/youtube/<slug>/

If no slug is provided:

• Check if the video filename or parent folder matches an existing ~/content/youtube/<slug>/ package
• If not, ask the user: "Which video package does this belong to?" and list existing packages from ~/content/youtube/

If the video path doesn't exist, ask the user for the correct path.

Step 2: Extract Audio

Extract the audio track from the video using ffmpeg:

ffmpeg -i "<video_path>" -vn -acodec libmp3lame -q:a 2 ~/content/transcripts/chapters_audio_<slug>.mp3 -y

This is faster and smaller than processing the full video file.

Step 3: Transcribe

Transcribe the extracted audio using the transcribe skill's script:

python3 ~/.claude/skills/transcribe/transcribe_video.py ~/content/transcripts/chapters_audio_<slug>.mp3

Read the resulting transcript file. It should contain timestamped segments.

Step 4: Identify Chapters

Analyze the transcript to identify natural chapter breaks. Look for:

• Topic transitions — When the speaker shifts to a new subject
• Section markers — Phrases like "next", "now let's", "moving on", "the first thing", "step one"
• Demo transitions — Shifts between talking and showing something
• Energy shifts — New introductions of concepts after a conclusion of the previous one

Generate 5-15 chapters depending on video length:

• Videos under 5 min: 3-5 chapters
• Videos 5-15 min: 5-10 chapters
• Videos 15+ min: 8-15 chapters

For each chapter:

• Timestamp in MM:SS format (or H:MM:SS for videos over 1 hour)
• Title — Short, descriptive, 2-6 words

The first chapter MUST be 0:00 - Introduction (or a more specific hook title).

Step 5: Read Existing Description

Read ~/content/youtube/<slug>/description.md if it exists. Identify:

• Is there an existing chapters section with [UPDATE] placeholders?
• What's the overall structure of the description?

Step 6: Present Chapters to User

Show the user the generated chapters:

0:00 - Introduction
0:45 - Setting Up the Project
2:12 - First Demo
...

Ask: "Do these chapters look right? Want to adjust any timestamps or titles?"

Step 7: Update Description

After the user approves (or after revisions):

If description.md exists with placeholder chapters:

• Replace the entire chapters section (the [UPDATE] placeholders) with the real timestamps

If description.md exists without a chapters section:

• Add a chapters section in the appropriate location (after the main body, before the CTA/links). Do not add a tags or hashtag line to the description — tags belong in tags.txt (YouTube tags field) only.

If no description.md exists:

• Create ~/content/youtube/<slug>/description.md with just the chapters section and a note to fill in the rest

Show the user the updated description and confirm the file was saved.

Step 8: Cleanup

Delete the temporary audio file:

rm ~/content/transcripts/chapters_audio_<slug>.mp3

Report what was done:

• Transcript location
• Updated description path
• Number of chapters generated

Rules

• Always extract audio first — don't try to transcribe the full video file directly (it's slower and larger)
• Chapters must start at 0:00 — YouTube requires this
• Chapter titles should be concise (2-6 words) — they appear in the progress bar
• Minimum 3 chapters for YouTube to recognize them as chapters
• Timestamps must be accurate to within ~5 seconds — round to clean numbers when the transition isn't instant
• Don't create chapters shorter than 10 seconds — YouTube may not display them
• When updating description.md, preserve all existing content outside the chapters section
• Clean up the temporary mp3 after transcription
• If the transcription doesn't have clear timestamps, estimate based on word count (~150 words per minute of speech)