<What it does, one line>. Trigger phrases: <phrases>.
日本語の概要は準備中です。原文の説明を表示しています。
End-to-end pipeline for producing Vox-style explainer videos from a single topic prompt. One topic in, finished film out — script, keyframes (Seedream 5.0 Pro), animation (Gemini Omni Flash), voiceover (xAI TTS), music (MiniMax Music 2.6), all assembled locally with ffmpeg via the Atlas Cloud API. Use this skill whenever the user asks for an explainer video, a Vox-style video, a documentary short, an educational video essay, a "one prompt to video" pipeline, or wants to turn a topic/article/report into a narrated video with subtitles and music. Also trigger when the user mentions Atlas Cloud video pipelines, keyframe-to-animation workflows, or automated video essays — even if they don't say "Vox."
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。
Produce a complete, narrated, subtitled, scored explainer video from a single topic. The pipeline runs in six stages, each producing artifacts the next stage consumes. Voiceover is generated BEFORE animation because VO duration drives all timing decisions.
TOPIC → 1.Script → 2.Voiceover → 3.Keyframes → 4.Animation → 5.Music → 6.Assembly
(Claude) (xAI TTS) (Seedream) (Omni Flash) (MiniMax) (ffmpeg)
ATLASCLOUD_API_KEY environment variable set (get one at atlascloud.ai — free credits on signup)ffmpeg and ffprobe installed (with libass for subtitle burning)requestsreferences/atlas-cloud-api.md)Before making any API calls, verify current endpoint paths and model IDs against https://www.atlascloud.ai/docs — media model APIs evolve quickly. The patterns in references/atlas-cloud-api.md were verified July 2026.
Create this layout for every film and keep it — every stage reads from and writes to it:
project/
├── brief.md # topic, angle, target length, audience
├── script.json # beats with narration, shot descriptions, captions
├── audio/
│ ├── vo/ # beat_01.mp3 ... beat_NN.mp3
│ ├── vo_durations.json
│ └── music.mp3
├── frames/ # keyframe_01.png ... style_anchor.png
├── clips/ # clip_01.mp4 ... (silent animated clips)
├── subs/ # captions.ass
└── final/ # film.mp4
You write this yourself. No API call. This is the stage that most determines quality — a great script with average visuals beats the reverse.
Read references/vox-style-guide.md (Writing section) before drafting. Core rules:
Write script.json:
{
"title": "Tang Golden Age",
"topic": "How Tang Dynasty China built the world's largest city",
"style_seed": "mixed-media paper collage, ink-wash Chinese mountains, vermillion red and aged cream palette",
"accent_color": "#C0392B",
"beats": [
{
"id": 1,
"narration": "In the seventh century, Tang China built Chang'an — the largest, richest city on Earth. The whole world came to its gates.",
"visual": "Emperor Taizong enthroned at center as paper cutout, court figures flanking, pagodas and ink-wash mountains behind, red seal stamp upper right reading 盛唐",
"caption_text": null,
"motion": "slow push-in on emperor, clouds drift left, subtle parallax between cutout layers"
}
]
}
caption_text is for on-screen kinetic typography moments (a key stat or term) — most beats leave it null; narration subtitles are handled at assembly. motion becomes the animation prompt in Stage 4.
Generate one audio file per beat, then measure durations. These durations are the master clock for the whole film.
Call the Atlas Cloud audio endpoint per beat (model: xAI TTS v1 — see references/atlas-cloud-api.md for the exact request shape and voice selection guidance). Pick ONE voice for the whole film. Vox register: measured, warm, slightly wry — avoid "movie trailer" voices.
After generation, probe every file and write audio/vo_durations.json:
ffprobe -v error -show_entries format=duration -of csv=p=0 audio/vo/beat_01.mp3
{"beats": [{"id": 1, "file": "audio/vo/beat_01.mp3", "duration": 9.83}], "total": 61.2}
Sanity-check total length against the brief. If a beat runs long, tighten the narration and regenerate that beat only.
One keyframe per beat, all in a consistent visual style. Consistency is the hard problem; solve it with the style anchor pattern:
bytedance/seedream-v5.0-pro/text-to-image for beat 1 (usually the title/hook frame). Build the prompt from the style block in references/vox-style-guide.md (Visual Grammar section) + the beat's visual + the film's style_seed and accent_color. Request 16:9, 2K.bytedance/seedream-v5.0-pro/edit with the anchor as a reference image (up to 10 refs supported; anchor + optionally the previous frame). Prompt: "Keep the exact art style, palette, paper-collage treatment, and border framing of the reference. New scene: {beat.visual}"This locks palette, texture, and framing across the film the way a human art director would.
Every prompt should end with the style suffix (see style guide), which encodes the Vox look: paper cutouts with white borders, halftone dots, tape strips, bold flat geometric accents, generous margins, single accent color.
Frames with caption_text set: instruct Seedream to render the text in a bold condensed sans, since Seedream 5.0 Pro's typography rendering is strong. Keep it under 5 words per frame.
Animate each keyframe into a clip via image-to-video. Target clip duration = that beat's VO duration + 0.5s of breathing room (round up to the model's supported increments).
Motion prompts for the collage aesthetic should be SUBTLE — this is the most common failure mode. The Vox look is "motion graphics," not "footage." Good motion vocabulary:
Explicitly forbid in every prompt: "no camera shake, no 3D rotation, no morphing of faces or text, no style drift, elements remain flat paper cutouts."
Poll each generation task to completion and download to clips/clip_NN.mp4. Generations fail or drift sometimes — review each clip; regenerate any where text warps or the style breaks. Budget for ~15% regeneration.
One instrumental bed for the whole film. Request is_instrumental: true — vocals fight the narration.
Prompt formula: {mood} {genre-adjacent texture}, {tempo}, {instrumentation}, {arc}. Example for a history piece: "contemplative cinematic underscore, felt piano and soft strings with light percussion pulse, 90bpm, builds gradually from sparse to full, documentary style". Match instrumentation to subject (guzheng/dizi textures for the Tang piece; analog synth pulse for a tech topic).
Music 2.6 generates fixed-length songs; if the track is shorter than the film, loop it at assembly with a crossfade; if longer, trim with fade-out. Never let the music arc fight the film arc — a mid-track drop landing on a quiet beat is jarring, so audition the result against the film's shape.
Read references/ffmpeg-assembly.md for full recipes. The sequence:
subs/captions.ass from the script — Vox-style burned-in subtitles: bold sans, white with heavy black outline, bottom-centered, max 2 lines, split narration at clause boundaries and time each chunk within its beat's window.-movflags +faststart.Final QC pass before delivering: watch for (a) subtitle/VO sync drift, (b) music overpowering narration, (c) a clip whose motion loops visibly, (d) style drift between frames. Fix at the stage where the problem originated, not with assembly hacks.
prompts.log file — reproducibility matters and users will want to tweak-and-regenerate single beats.beats × ($0.10 image + ~$1.20 per 10s clip) + ~$0.50 audio.references/vox-style-guide.md — read before Stage 1 and Stage 3. The visual grammar, writing voice, and prompt templates.references/atlas-cloud-api.md — read before Stage 2. Endpoints, model IDs, async task pattern, polling code, costs.references/ffmpeg-assembly.md — read before Stage 6. Conform, concat, subtitle, ducking, and encode recipes.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
<What it does, one line>. Trigger phrases: <phrases>.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill whenever the user wants to create or improve a presentation for an academic context — conference papers, seminar talks, thesis defenses, grant briefings, lab meetings, invited lectures, or any presentation where the audience will evaluate reasoning and evidence. Triggers include: 'conference talk', 'seminar slides', 'thesis defense', 'research presentation', 'academic deck', 'academic presentation'. Also triggers when the user asks to 'make slides' in combination with academic content (e.g., 'make slides for my paper on X', 'create a presentation for my dissertation defense', 'build a deck for my grant proposal'). This skill governs CONTENT and STRUCTURE decisions. For the technical work of creating or editing the .pptx file itself, also read the pptx SKILL.md.
日本語の概要は準備中です。原文の説明を表示しています。
Shortest English alias for web-adapt / universal-web-adaptation. Use this when adapting an unfamiliar public website generically before creating any site-specific rules.
日本語の概要は準備中です。原文の説明を表示しています。
Use this skill to audit CLI adapter projects (like opencli) for missing output fields, then batch-generate fixes and submit PRs. Turns AI agents into adapter quality reviewers.
日本語の概要は準備中です。原文の説明を表示しています。
Operate professional paid advertising across Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, and X. Use for account intake, source-grounded audits, strategy, budget and measurement planning, creative production, experiments, reporting, monitoring, and explicitly approved campaign changes. Also trigger on PPC, paid social, retail media, attribution, tracking, landing pages, cross-platform conversion totals, negative keywords or search terms, beta-feature scoring, stale platform claims, API-token or credential setup, campaign deletion, and safe Claude Ads installation or uninstall.
日本語の概要は準備中です。原文の説明を表示しています。
Audit Amazon Ads profiles, regions, Sponsored Products, Sponsored Brands, Sponsored Display, DSP, portfolios, targeting, search terms, retail readiness, creative, budgets, ACOS, TACOS, reporting, and policy. Use for Amazon Ads, sponsored ads, Amazon PPC, ACOS, TACOS, ASIN advertising, Amazon DSP, or retail-media optimization.
日本語の概要は準備中です。原文の説明を表示しています。