mcpbeat

Render Editorial Motion Podcast

gooseworks-ai/render-editorial-motion-podcast

Assemble an editorial-motion podcast-clip ad from a config — a real clipped podcast MP3 carries the narrative while N flat 2-tone editorial-illustration keyframes are animated NOT by generative i2v but by DETERMINISTIC ffmpeg ken-burns (zoompan) + hard cuts (no crossfades, which expose geometric drift), each beat snapped to its spoken line, the real audio muxed, Whisper-driven captions burned only mid-sentence, and closed on a PIL brand end card — never AI-rendered text. This is the FREE deterministic assembly stage (ffmpeg ken-burns + hard concat + audio mux + captions + end card); the real audio is clipped from source and the keyframes come from create-image-fal. Use for the editorial-motion-podcast format.

8k tokens
context cost
the whole folder, loaded on every use
6
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
1086
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/gooseworks-ai/goose-skills --skill render-editorial-motion-podcast

What comes with it

27 953 bytes besides the instruction
scripts/PIPELINE.md
scripts/README.md
scripts/config.example.json
skill.meta.json
tests/smoke-test.md

The instruction itself

3 sections, as written by the author

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):

  • 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.

  • 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.

  • 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.

How to use it

Copy the folder

Take gooseworks-ai/render-editorial-motion-podcast from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

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