資料には具体的なスキルの内容や手順が記載されていないため、用途や得られる結果を特定できません。
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シーン動画をナレーションに合わせて編集し、実商品写真のエンドカードや音楽、字幕を加えて縦型広告に仕上げます。
Assemble an absurdist animated-explainer video ad (~38s, 9:16) from per-scene i2v clips + their measured VO windows — retime each clip to its VO, re-encode every segment to identical 30fps/libx264/yuv420p so the concat demuxer never drops frames, concat, build a REAL-product PIL end card (never AI) held static, mix VO (loudnorm I=-14) under music (loudnorm I=-26, volume 0.62, amix normalize=0), and burn libass captions last. FREE deterministic assembly (bash-free, Python + ffmpeg + PIL); the recipe supplies the clips, VO, music, product photo, palette, and caption table and gates the paid keyframe/clip/VO/music calls to their own capabilities. Use for the absurdist-explainer format.
実行スコア 未検証
インストール方法を見るシーンごとの動画、ナレーション、音楽、商品写真などを受け取り、約38秒・縦型9:16の解説広告に組み立てます。各クリップを計測済みのナレーション時間に合わせて調整し、全シーンを同じ30fpsの形式に再エンコードしてから連結します。実際の商品写真を使った静止エンドカードを作り、ナレーションと音楽の音量を整えてミックスし、最後に字幕を映像へ焼き込みます。
このスキルが担うのは素材の組み立てです。ストーリー、キャラクター、画風、ナレーター、音楽などの生成や演出判断は上流のレシピで行い、設定とファイルを受け取ります。編集工程はPython、ffmpeg、PILで実行し、字幕やエンドカードの文言、配色は設定に従います。字幕はシーンごとに一つの表示で、発話中の単語に合わせて細かく同期する形式ではありません。
生成済みのシーン動画や音声素材を、広告として一本の縦型動画にまとめたいときに向いています。ナレーションの長さに合わせたカットや、実商品の画像を使った締め画面が必要な制作にも使えます。
Python、ffmpeg、PILが必要です。生成素材や商品写真、設定ファイルは別途用意します。この工程自体は有料の生成APIを呼び出しません。
この紹介文は、公開されている SKILL.md をもとに AI(OpenAI Codex)が作成しました。正確な仕様は下の原文を確認してください。
インストールする前に、エージェントに与えられる指示の中身を確認できます。
The free, deterministic renderer for the absurdist-explainer video ad format — an animated spot that explains one problem and how the product fixes it. The format is the mechanics: show the problem in a funny, exaggerated cartoon way, teach the product's ownable mechanism visually, show what the problem costs, bring the product in, land the fix as the climax, pay it off, end on a real-product card. One narrator voice carries the whole spot. How the story is told (problem → fix, how it works, a day in the life, the product as hero, or a villain arc) is the user's choice, made upstream. This capability is the FREE assembly stage only. All generative work (nano-banana keyframes, Seedance i2v clips, ElevenLabs VO + music) happens upstream in the recipe and is handed to this capability as files.
It ports the compose recipe validated on two earlier reference runs (both happened to use the villain arc). The recipe is deterministic — iterate the cut for free, re-roll only the offending paid beat.
The creative calls are made upstream by the recipe's choices and arrive here only as
files and config values. This renderer is story- and style-agnostic: it never assumes a
story shape, a cast, a look, a narrator or a music style.
story_shape — how the story is told: problem → fix (no villain) / how it works /
a day in the life / the product as hero / villain arc (the problem as a cartoon villain
who schemes and loses). Reaches this capability as the per-scene caption text and the
VO files. Asked of the user; the demo used the villain arc.cast — who the cartoon characters are (the customer, the product as a character,
a mascot; a personified problem only on the villain arc). Reaches this capability only
inside the clips. Asked of the user.narrator — who speaks the single VO track. Arrives as the scenes[].vo files.
Asked of the user; the demo used the villain (villain arc only).visual_style — the art style of the i2v clips (scenes[].clip). Asked of the
user; the demo used Pixar-style 3D. Nothing here depends on it.narrator_voice — the voice cast for the VO. Asked of the user; the demo used a
characterful male villain voice.music — the bed at music_bed. Asked of the user; the demo used whimsical
pizzicato + woodwinds + xylophone. The mix constants below apply to any style.scale=1080:1920:force_original_aspect_ratio=increase,crop=1080:1920,fps=30,setsar=1,
then tpad=stop_mode=clone if the VO is longer than the clip, else a trim). Each
window is snapped to a whole number of frames first. compose.py and
make_captions.py use the same rule, so video cuts, VO windows and caption cues share
the same cut times and a caption never outlives its cut.libx264 -crf 18 -pix_fmt yuv420p -r 30 even if already correct — a framerate mismatch makes the concat demuxer silently
drop frames.-c copy).build_endcard.py composites the REAL retail product photo
over the brand palette (flat, or sampled from the photo's own edge pixel) with a typeset
wordmark + claim rows + CTA pill in PIL ImageDraw.text — never an AI cartoon bottle,
never AI-rendered brand text. compose.py holds it static over the dwell. Set
end_card.zoom_to above 1.0 (for example 1.04) only if you want a slow zoom.
Text that would be hard to read on its background (a dark brand colour on a dark
photo) is drawn in white or near-black instead, with a warning. If end_card.vo is
set, that spoken line plays from the start of the end-card window, and the dwell is
stretched to at least the line's duration + 0.5s.loudnorm I=-14 TP=-1.5, music bus loudnorm I=-26 TP=-3 then
volume=0.62, amix inputs=2 duration=first normalize=0, so the music is ducked
under the VO.compose.py prints the measured loudness and peak.make_captions.py emits a libass .ass (one cue per scene, Arial 64
white / 6px outline / MarginV=330, start = scene_start + 0.08s, suppressed on the end
card). compose.py burns it as the final filter so captions sit on top.scripts/build_endcard.py — PIL composite of the real product photo + typeset brand
layer (wordmark / product line / claim rows / accent CTA pill). Reads the same
config.json. Run this FIRST so end_card.image exists before compose.py.scripts/make_captions.py — emits the per-scene libass .ass from the SAME scene table
compose reads, so caption windows stay in lockstep with the cut. Run before compose.py
(or point config.captions_ass at nothing to skip captions).scripts/compose.py — the assembler: per-scene retime + identical 30fps re-encode →
concat -> static end card (voiced if end_card.vo is set) -> VO/music loudnorm mix
-> master loudness pass -> burn captions -> master mp4.scripts/config.example.json — the shape of the config the recipe binds. Its values
are a labelled worked example (the demo build: a villain-arc story where Rust
loses to Glidefern, a made-up bike-chain wax).
Captions, end-card copy and palette come from the user's brand and choices — never copy
them as defaults.--config + a runtime work dir — NO hardcoded paths)config.json carries: scenes[] (each {id, clip, target_sec, vo, caption, atempo?}
where target_sec is the measured VO window), end_card{product_image, image, dwell_sec, zoom_to?, wordmark, product_line, claims[], cta, background?, vo?}, brand_palette {primary, primary_lite, accent, grey}, music_bed, music_volume (default 0.62),
atempo (compose-stage VO speed-up, default off; the reference runs used 1.3 when the VO
read slow), captions_ass, and caption_style. See config.example.json.
end_card.vo (optional) is the path to the end card's spoken line. It is laid at
the start of the end-card window. The dwell becomes the larger of dwell_sec and the
line's duration + 0.5s. Leave it out for a silent end card (music only).
end_card.atempo overrides the global atempo for this line.C:/...), captions_ass too.ImageDraw.text. AI draws the world + characters only.target_sec is the MEASURED VO duration (ffprobe each VO mp3), never a planned word
count — VO drives the per-scene timing.volume 0.62 to 0.70
(the two reference runs), amix normalize=0. Master target -14.5..-13.5 LUFS,
true peak <= -1.5 dBFS. The master pass enforces this and prints what it measured.start = scene_start + 0.08s, suppressed on the end card (its typeset copy
carries the message — two text layers at one spot are both unreadable).watch (QC the final master - confirm every character's look holds, the single
narrator voice carries the whole spot, no AI brand text leaked into a cartoon
background, the end card is the real product, and duration is within 0.1s of the summed
windows plus the end-card dwell). The recipe gates the paid create-image-fal (keyframes), create-video-fal
(Seedance i2v), create-vo-elevenlabs, and create-music-elevenlabs calls to their own
capabilities — this capability itself makes NO paid calls.
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資料には具体的なスキルの内容や手順が記載されていないため、用途や得られる結果を特定できません。
顧客の課題や商品情報、広告事例を調べ、根拠のある広告訴求と静止画・動画・コピー案にまとめます。動画案は実際の制作フォーマットとの相性も確認し、商品単位の角度集として整理します。
Google、Meta、LinkedInなどの広告実績を分析し、成果の出た広告や予算の無駄を特定します。停止・拡大・テスト案や、具体的な予算配分を提案します。
広告費と登録後の成果を照合し、質の高いリード獲得にかかった実コストを算出します。広告素材ごとに拡大・維持・調査・停止の判断材料を整理するスキルです。
Meta広告を始める前にブランド情報を調べ、予算や広告表現に関わる不明点だけを質問して準備を整えます。確認事項と仮定を記録し、ブランド情報とキャンペーン概要を作成します。
広告文や画像内の表現を配信先と商品カテゴリのルールに照らして確認し、直せる箇所を修正しながら、法務や人の判断が必要なリスクを広告ごとに整理します。