Install in seconds
Install this skill
Copy the command and run it in your terminal. You can review the source before installing.
terminal
git clone https://github.com/gooseworks-ai/goose-skills

Works with Git. The repository opens in your current directory.

🎙️
AutomationPython

Editorial Motion Podcast

by gooseworks-ai

Assembles a podcast-clip ad from a config using deterministic ffmpeg ken-burns, hard cuts, burned captions, and a PIL end card. Use it when you have clipped narration audio, beat-synced keyframes, and need a finished vertical master.

1.1K stars194 forksAdded 2026/07/20
claudeclaude-skillsclaudecodeclaudecode-skillscodexcursorgtmskills

Documentation

README

render-editorial-motion-podcast

Assemble an editorial-motion podcast-clip ad from a config: a real clipped podcast audio line carries the whole narrative and every visual beat is timed to the sentence it describes, in a bold flat 2-tone editorial-illustration look ("a New Yorker spot-illustration that moves"). The motion is not generative video but deterministic ffmpeg ken-burns on static keyframes, so it reads as a printed page that moves. This capability is that FREE, deterministic assembly — the ffmpeg motion, hard-concat, audio mux, caption burn, and PIL end card.

scripts/config.example.json is the worked example (Klarify "Rat Park", ~40.8s 1080×1920 9:16, 6 beats); scripts/PIPELINE.md maps every config block to its source step and scripts/README.md documents the free assembly.

Run

This is the FREE, deterministic assembly stage — it spends nothing on the motion layer. The paid inputs are separate: the real podcast MP3 is clipped from source (free ffmpeg) with its Whisper word timings, and one editorial-illustration keyframe per beat (chained ref images so cage/character geometry holds) comes from create-image-fal (Nano Banana). Given the clipped audio + words.json + the per-beat keyframes + the real brand wordmark PNG, render-editorial-motion-podcast renders each keyframe as a ken-burns segment, hard-concats on the beat, muxes the real audio, burns the mid-sentence captions, and composites the PIL end card → the master. Re-cuts reuse the existing audio / keyframes and cost $0.

Contract (the free assembly)

  • A spoken narration carries the whole spot — no generated SONG. Mux the provided narration MP3 (-map 0:v:0 -map 1:a:0) — a real clipped podcast line (preferred) OR an approved generated VO (create-vo-elevenlabs). Never a sung/generated track. (Clip-vs-generate is the recipe's STEP-0 intake decision — if no source episode is supplied, ASK the user.)
  • NO generative i2v — deterministic ffmpeg ken-burns only. Animate each static keyframe with zoompan (push-in / pull-back, 1.0→~1.06×, 24fps); Seedance/Kling are photoreal-trained and invent naturalistic middle states that collapse the 2-tone look. Never -loop 1 with zoompan d=N (it balloons the duration); feed a single image and clamp with -t + trim.
  • Hard cuts on the beat — no crossfades. Crossfades ghost two drifting cages through each other; hard-concat each beat's segments and split long beats into micro-cuts (target 8–10 distinct visual moments). Each beat's visual STARTS within ~0.5s of its spoken line.
  • Captions from Whisper word-timestamps, ON only mid-sentence. Burn frosted-subtle captions while the speaker talks; leave silent/reflective beats and the end card uncaptioned. THREE mandatory rules (each bit us in prod — bake them in):
    1. NON-OVERLAP — clamp every line to END before the next STARTS (end = min(last_word_end + ~0.15, next_start - 0.03)). Two boxes must never stack at the same spot; an end-tail bleeding into the next window is the #1 caption bug.
    2. SAFE AREA — captions sit in the lower third, so the keyframe's subject must stay in the upper ~75% (see the recipe's look_pack.caption_safe_area). If a finished keyframe's subject intrudes into the caption band, deterministically shift the subject UP into the empty top space (PIL: paste up ~0.24H onto a canvas pre-filled with the exact paper color from a clean corner) — never let the box sit on the subject.
    3. BURN ENGINE — prefer libass (ass/subtitles filter), but check ffmpeg -filters first: many builds (Homebrew) lack libass/drawtext. If absent, use the deterministic overlay fallback — render each line as a transparent PNG (frosted rounded box + white text, PIL) and composite via the ffmpeg overlay filter with timed enable='between(t,st,en)' windows. Same look, no libass.
  • End card via PIL from the real wordmark PNG — never AI-render brand text. The lockup is composited deterministically (stretched-gradient bg + feathered mascot crop + wordmark + tagline with a system font); a diffusion model garbles a wordmark ("therapits"). The video runs a ~1.5s silent hold past the audio on the end card (fade first/last 0.3s).
  • FFmpeg composite, deterministic, FREE. Ken-burns each keyframe, hard-concat, mux the real audio, burn the captions, hold on the end card → a 1080×1920 h264+aac master. No paid calls.

More from gooseworks-ai

Other Claude Code skills by this author in the directory.