vox-director
Turn one topic into a finished Vox-style paper-collage explainer/ad video — automated end to end on Atlas Cloud + ffmpeg. An agent skill.
- 评测生成时间(北京时间)
- 本报告引擎
- v3.10.0
- 当前引擎
- v3.16.0
本报告与当前引擎使用不同规则;原分数不会自动更新,不同版本的分数不宜直接对比。
进入后确认来源与额度,提交才会创建任务。
综合采用结论
核心能力可用,建议在受控范围内试用
- 基础评测完成+25/25确定性评分与静态安全扫描已完成
- README 有效证据+16/256,365 个去重后的有效字符
- 独立证据来源+4/201 类非重复证据,重复文件不叠加
- 仓库元数据+10/10已取得仓库状态与采用数据
- 活跃记录+5/5已取得最近提交时间
- AI 复核+15/15已完成结构化 AI 证据复核
图示结构未通过校验
AI 返回了图示候选,但字段数量、长度或格式未满足图示约束。为避免展示错误关系,本次仅保留已验证的文字证据;重新评测会再次尝试生成。
- README中'How it works'部分描述了从主题到final.mp4的流程
- 安装部分提供了git clone命令和API key设置
- 模型表格列出了具体模型和用途
- Quick start部分给出了示例提示词
- Requirements部分列出了ffmpeg、Python等依赖
- 问题与用途描述
- 有效 README
- 安装或接入步骤
- 可执行示例
- 未发现已知高风险模式
- 缺少输出或结果说明
- 缺少限制、权限或边界
- 缺少错误处理或排障
- 缺少输出格式和结果说明
- 缺少错误处理和排障指南
需要快速生成Vox风格解释视频的内容创作者、使用Claude Code或Codex等编码代理的开发者、有Atlas Cloud API密钥和ffmpeg环境的用户、希望自动化视频制作流程的团队
没有Atlas Cloud API密钥或ffmpeg的用户、需要完全本地化或离线运行的场景、对视频内容有严格版权或隐私要求的项目
也有自己的公开项目?先看完证据,再用当前规则生成独立报告。
评测我的项目 →静态扫描不是安全保证,生产接入前仍应人工复核权限和数据边界。
- 01补充输出或结果说明
- 02补充限制、权限或边界
- 03补充错误处理或排障
方法、证据与局限展开收起
GitHub Repository API
1 个文件 · 7,883 字符
v3.10.0 · AI 复核已启用(deepseek-chat)
- 静态评测不会安装或执行项目代码
- 安全扫描基于高信号文件与已知模式,不能替代人工审计
- 流行度只反映采用程度,不代表安全或工程质量
30 天热度趋势
README
English · 简体中文
🎬 Vox Director
Turn one topic into a finished Vox-style paper-collage explainer / ad video — script, collage keyframes, motion, voice-over, music and captions, all automated.
An agent skill that runs end to end on the Atlas Cloud API + local ffmpeg, usable by any coding agent (Claude Code, Codex, etc.). You give it a one-line topic; it gives you an mp4.
https://github.com/user-attachments/assets/ed08d230-7bcb-4b48-a17d-23c079208f9f
▶ "The evolution of Chinese civilization" · 30s
| Football history · 60s | Mexican street food · 60s | A brief history of money · 60s | Silicon Valley history · 60s |
▶ more films — click any thumbnail to play
What it is
The look is the modern editorial paper-collage popularized by Vox explainers: hand-cut paper cut-outs, torn edges, tape, halftone dots, newspaper clippings, bold flat color per beat, big cut-out headlines — brought to life with motion, a narrator, music and captions.
How it works
One topic flows through one script per stage, all driven by a single beats.json per project:
topic
│
├─ 1. beat map pick a narrative arc → write beats.json ◀── GATE 1: you approve the beat map
├─ 2. style bake-off render the same beat in 3–4 themes ◀── GATE 2: you pick the look by eye
├─ 3. keyframes one collage poster per beat (nano-banana-2)
├─ 4. motion animate each poster (gemini-omni-flash i2v)
├─ 5. voice + music one narrator (xai/tts) + BGM (minimax/music)
├─ 6. assemble ffmpeg: concat, duck music under VO, burn captions + watermark
└─ final.mp4
That flow is B-roll — a topic in, everything generated. Two more input modalities reuse the same engine:
- A-roll — you already have a talking-head video. It is ASR-segmented into beats and re-styled into the collage look, keeping the real face, lip-sync and gestures frame-for-frame (
gemini-omni-flash/video-edit, auto-retrying onseedance-2.0/reference-to-video). - C-roll — you have one still photo (a selfie, a product shot). The subject is cut out as a photographic sticker — never redrawn — and each beat's poster is generated around it (
nano-banana-2/edit). The narration can be cloned into the subject's own voice.
Two ideas make or break the result, and the skill is built around both:
- The look is born in the image step. Each beat is a finished collage poster. All the collage DNA (torn paper, cut-outs, halftone, headline text) lives in that image — if the poster isn't a rich collage, nothing downstream saves it.
- The motion is added after. By default an AI video model animates the whole poster (the "living poster" path). For dramatic piece-by-piece assembly, an optional local keyframe engine cuts the poster into parts and drives them frame-by-frame (no content filters, pixel-exact — great for real people).
Two human decision gates keep you in control (approve the beat map; pick the style); everything else is automated.
Models (verified on Atlas Cloud)
| Job | Model |
|---|---|
| Keyframe / collage poster | google/nano-banana-2/text-to-image |
| Animate (non-real content) | google/gemini-omni-flash/image-to-video |
| Animate (real people / brands) | kwaivgi/kling-video-o3-pro/image-to-video |
| Re-style a talking-head (A-roll) | google/gemini-omni-flash/video-edit |
| Anchor a photo in the collage (C-roll) | google/nano-banana-2/edit |
| Narration | xai/tts-v1 |
| Narration in a real person's voice | bytedance/seed-audio-1.0 (voice cloning) |
| Music | minimax/music-2.6 |
| Cut out an element (advanced path) | youchuan/v8.1/remove-background |
Model IDs drift — the skill fetches the live list from GET https://api.atlascloud.ai/api/v1/models before running.
Install
This is an agent skill — it works with any coding agent that can read a workflow and run scripts (Claude Code, Codex, …). Claude Code auto-discovers it as a skill; other agents read AGENTS.md → SKILL.md.
Option A — from this repo:
git clone https://github.com/Alisa0808/vox-director.git ~/.claude/skills/vox-director
Option B — from the packaged skill: download vox-director.skill and install it via your Claude skills UI.
Then set your Atlas Cloud API key (get one at atlascloud.ai/console/api-keys):
export ATLASCLOUD_API_KEY="sk-..."
Quick start
Just ask your coding agent, with the skill installed:
"Make me a Vox-style collage video introducing Mexican street food — English, 16:9, 15 seconds."
The agent will draft a beat map for your approval, run a style bake-off for you to pick from, then generate keyframes → motion → voice → music and assemble out/<project>/final.mp4.
Requirements
- A coding agent — Claude Code, Codex, or similar
- Atlas Cloud API key
- ffmpeg + ffprobe (
brew install ffmpeg) - Python 3 with Pillow (
pip install pillow) — for caption/watermark overlays
What's in the box
SKILL.md the skill (English) — the workflow the agent follows
SKILL.zh.md the same skill in Chinese
AGENTS.md entry point for non-Claude agents (Codex, …)
references/ the creative engine
prompt-guide.md the LOOK layer — prompt structures, vocab & 9 theme presets
beat-layer.md 14 narrative arcs + hook/pacing + shot patterns
voices.md xai/tts voice roster — pick a voice_id per language/tone
models-and-gotchas.md every API / ffmpeg gotcha, already solved
local-engine.md the advanced element-level motion engine
scripts/ one script per pipeline stage
examples/ ready-to-run beats.json examples
assets/ the showcase film
Credits
Built by @alisaqqt — follow for more agent-skill experiments.
Inspired by the collage-ad workflows of Stav Zilber, rom1trs and Higgsfield, and by Vox's explainer visual language.
Built end to end on Atlas Cloud — one prompt, one film.
License
MIT © 2026 Alisa Qian