agentleFS
jackzhaojinjackzhaojin/ai-builder-kit/skills/podcast-slides-video/SKILL.md

podcast-slides-video

Skill1 starsChanged 2 months agoApache-2.0View on GitHub

Build a YouTube-ready MP4 from narrated audio plus a slide deck: a NotebookLM audio overview or podcast about a talk, a recorded voice track, a narrated walkthrough, matched to the deck's slides (PDF or PPTX) with slide changes cut to the transcript. Use this whenever the user has an audio file and slides and wants a video out of them, even if they never say "video": "put my slides to this audio", "turn the NotebookLM podcast into something I can upload", "sync the deck to the narration", "make a YouTube version of my talk from the deck and this recording", "the audio kind of maps to the slides". Produces the MP4, a cue sheet that is the auditable edit decision list, a validation pass with a contact sheet, and a YouTube chapter list. Not for editing existing video footage (use video-trim for that) and not for generating narration.

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 1 is distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Run it in the background and do step 3's deck reading while it transcribes.

    line 44
  2. Very specific:

    Read deck-text.txt (and look at the slide PNGs, at least a contact sheet), then read transcript.md end to end.

    line 48
  3. Very specific:

    Read references/cutting-guide.md before writing the cues.

    line 53

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Podcast + slides -> YouTube video

Turn "audio that talks about a deck" into a video where the right slide is on screen while it is being talked about. The only judgment step is placing the cuts; everything else is a bundled script. Working files go in a gitignored folder next to the source material (the user's convention is local-only/ or trim-work/; ask only if the project has neither and nothing obvious fits).

Requirements

ffmpeg, ffprobe, pdftoppm, pdftotext (Homebrew ffmpeg + poppler), uvx (from uv) for MLX Whisper on demand, Python 3 (the validator's Pillow and numpy come from its inline metadata via uv run). LibreOffice soffice only if the deck arrives as PPTX. Apple Silicon assumed for whisper; see references/ffmpeg-notes.md item 7 otherwise.

Workflow

1. Probe and set up (1 min)

Confirm the audio duration and the deck page count, and that the deck is the version the audio was made from (a NotebookLM overview generated from draft N does not always match deck N+1; say so if the transcript talks about slides that no longer exist). Pick the workdir and make sure it is gitignored.

2. Mechanical prep (2 to 4 min, mostly whisper)

bash scripts/prep.sh "<audio>" "<deck.pdf|pptx>" "<workdir>"

Renders slides/slide-NN.png at 1920x1080, dumps deck-text.txt, extracts 16 kHz mono audio, transcribes with whisper large-v3-turbo (word timestamps), writes transcript.md (one timestamped segment per line). Run it in the background and do step 3's deck reading while it transcribes.

3. Cut the cue sheet (the judgment step)

Read deck-text.txt (and look at the slide PNGs, at least a contact sheet), then read transcript.md end to end. Write <workdir>/slide-timeline.json: one cue per slide change, each with start (when the crossfade into the slide begins), anchor (the transcript line it is timed to), note (why), and chapter on cues that should start a YouTube chapter. Start from assets/slide-timeline.example.json.

Read references/cutting-guide.md before writing the cues. The short version: cut on the sentence that introduces the next slide's idea, about 0.3 s before it; hold the title card through the cold open; going back to an earlier slide is fine when the audio does; cut the closing recap as a montage of 8 to 18 s per slide; nothing under 5 s; no invented visuals for stretches that have no slide.

4. Render (about 1/5 of the audio length)

python3 scripts/build_video.py <workdir>/slide-timeline.json -o <workdir>/<name>.mp4 --dry-run   # check the math
python3 scripts/build_video.py <workdir>/slide-timeline.json -o <workdir>/<name>.mp4             # background it

Name the output after the deck plus a date stamp (the user's convention: <topic>-v<yyyy-mm-dd>-vN). The script writes the filtergraph and a .build.json sidecar next to the MP4 for audit. Source audio is stream-copied when it is AAC, so there is no generation loss.

5. Validate (2 min) - do not skip, do not hand-wave

uv run scripts/validate_video.py <workdir>/slide-timeline.json <workdir>/<name>.mp4
bash scripts/check_anchors.sh <workdir>/<name>.mp4 <workdir>/slide-timeline.json 5

The validator must end with ALL CHECKS PASSED: container params, the correct slide on screen after and before every cut, the fade-out ramp, and audio identical to the source. Open the .cue-check.png contact sheet it writes and actually look at it. check_anchors.sh re-transcribes five windows from the finished MP4; each anchor sentence should appear in the second half of its window. If a cut is off, fix the cue sheet and re-render; do not patch the video.

6. Chapters and hand-off

python3 scripts/make_chapters.py <workdir>/slide-timeline.json > <workdir>/youtube-chapters.txt

Send the MP4 and the contact sheet to the user. Write a short README in the workdir (inputs, outputs, how to re-render) so the folder explains itself later, and append an entry to the project's memory/log file if it keeps one. Do not upload anywhere. Mention anything in the audio a careful colleague would flag (a quote attributed to the deck that is only in the talk track, a number the user's guardrails care about), without changing the audio: it is the user's pick.

Bundled scripts

  • scripts/prep.sh - deck to PNGs + text, audio to 16 kHz wav, whisper transcript, readable transcript.
  • scripts/transcript_dump.py - whisper JSON to [mm:ss.s - mm:ss.s] text lines.
  • scripts/build_video.py - cue sheet to MP4 via an xfade chain; --dry-run prints durations + command.
  • scripts/validate_video.py - every check above + contact sheet; exit 1 on failure.
  • scripts/check_anchors.sh - re-transcribe windows around cuts from the MP4.
  • scripts/make_chapters.py - YouTube chapter list from cues carrying chapter.
  • assets/slide-timeline.example.json - cue sheet template with every field.
  • references/cutting-guide.md - how to place cuts; read before step 3.
  • references/ffmpeg-notes.md - the xfade math, encoder settings, gotchas (tail seek, whisper naming, non-AAC sources, 4:3 decks).

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