AI video production skill for agents: HeyGen avatars, Seedance b-roll, OpenAI images, Remotion, HyperFrames, screen recording, FFmpeg captions and QC.
272
stars
13
commits
Python
primary language
Aug 9, 2026
updated
Built by the team at Distribb — the SEO and growth autopilot for operators.
→ Build and scale content systems with us at distribb.io.
An end-to-end AI video production skill for agentic coding frameworks. Give your Cursor, Claude Code, or other shell-capable AI agent a video idea, source link, product flow, screen recording, or script, and this skill teaches the agent how to turn it into a polished video using HeyGen avatars, screen recordings, AI b-roll, OpenAI image generation, Remotion, HyperFrames, FFmpeg, captions, music, and quality-control loops.
This repo is designed to be dropped into an AI agent project as a reusable skill. It includes the actual instruction file (SKILL.md), deep production references, workflow examples, FFmpeg recipes, Python tools, and starter Remotion/HyperFrames templates.
The flagship format is:
Avatar Explainers (avatar-explainer) — proof-driven videos with a synthetic presenter, source receipts, screen recordings, UI micro-stories, captions, and action takeaways.
Most AI video tools stop at one layer:
Real videos need the whole pipeline:
This skill gives an AI agent the operating system for that process.
super-video-maker-skill/
├── SKILL.md # Main agent instructions
├── REFERENCE.md # Provider choices, design logic, quality gates
├── WORKFLOW_EXAMPLES.md # Full recipes, including Avatar Explainers
├── FFMPEG_PLAYBOOK.md # Practical FFmpeg recipes
├── REMOTION_VIDEO_GUIDE.md # Remotion production style guide
├── requirements.txt # Python dependencies
├── package.json # Root JS tooling dependencies
├── .env.example # Environment variable template
├── tools/
│ ├── heygen_client.py # HeyGen avatar generation + polling + download
│ ├── replicate_video.py # Seedance 2.0 via Replicate (legacy fallback)
│ ├── image_provider.py # OpenAI image generation/editing helper
│ ├── screen_recorder.py # FFmpeg/Xvfb or Playwright screen recording
│ ├── agent_browser_recorder.py # Agent-operated browser proof recording
│ ├── demo_video_composer.py # Polished product demo composer
│ ├── video_captioner.py # Whisper + ASS captions + shorts rendering
│ ├── music_provider.py # ElevenLabs music helper
│ ├── local_explainer_broll.py # Local fallback b-roll renderer
│ ├── broll_layout_qc.py # Visual layout QC contact sheets
│ └── ffmpeg_qc.py # Final technical QC
├── remotion-template/ # Starter Remotion project
└── hyperframes-template/ # Starter HyperFrames/HTML timeline
Clone the repo:
git clone https://github.com/Bomx/super-video-maker-skill.git
cd super-video-maker-skill
Install Python dependencies:
python3 -m venv venv
source venv/bin/activate
pip3 install -r requirements.txt
python3 -m playwright install chromium
Install JavaScript dependencies if you want Remotion or HyperFrames:
npm install
cd remotion-template && npm install && cd ..
cd hyperframes-template && npm install && cd ..
Install system dependencies:
brew install ffmpeg
On Linux servers you may also need:
sudo apt-get update
sudo apt-get install -y ffmpeg xvfb
Create your environment file:
cp .env.example .env
Then fill in the keys you plan to use.
Minimum useful setup:
HEYGEN_API_KEY=
HEYGEN_AVATAR_ID=
HEYGEN_VOICE_ID=
OPENAI_API_KEY=
REPLICATE_API_TOKEN=
ELEVENLABS_API_KEY=
Optional:
AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=
AWS_REGION=us-east-1
AWS_S3_BUCKET=
SOUNDTRACKS_S3_BASE_URL=
ANTHROPIC_API_KEY=
Provider notes:
HEYGEN_AVATAR_ID and HEYGEN_VOICE_ID are separate values.Never commit .env, cookies, generated videos, recordings, or user sessions.
Copy the folder into your project:
mkdir -p .agents/skills
cp -R super-video-maker-skill .agents/skills/super-video-maker
Then ask your agent:
Use the super-video-maker skill to create an avatar explainer about this topic...
Place SKILL.md and the supporting files wherever your framework loads skills or system prompts from. The important part is that the agent can read:
SKILL.md,REFERENCE.md,WORKFLOW_EXAMPLES.md,FFMPEG_PLAYBOOK.md,REMOTION_VIDEO_GUIDE.md,tools/ directory.If your framework does not support skills natively, paste SKILL.md into the agent's system prompt and keep the rest of the files in the working directory.
Example prompt to your agent:
Use the super-video-maker skill.
Make a 90-second Avatar Explainer about a trending SEO topic.
Use a recent X.com post as a trend signal, but verify the claims with official sources.
Use my HeyGen avatar.
Use screen/source receipts and UI micro-stories.
Do not make generic AI b-roll.
Pause before paid HeyGen/OpenAI/Replicate calls and show me the plan first.
Expected agent flow:
broll_layout_qc.py.ffmpeg_qc.py.Use avatar-explainer when the video combines:
The default structure:
Hook
→ casual avatar disclosure
→ news/update beat
→ concrete example
→ source proof
→ action steps
→ spoken CTA tail over outro card
Important rules:
Generate a HeyGen avatar clip:
python3 tools/heygen_client.py \
--script-file script.txt \
--output tmp/video_jobs/my_job/avatar.mp4 \
--avatar-id "$HEYGEN_AVATAR_ID" \
--voice-id "$HEYGEN_VOICE_ID"
Generate Seedance b-roll:
python3 tools/replicate_video.py generate \
--prompt "documentary-style browser research shot, source receipt, modern editorial pacing" \
--duration 7 \
--resolution 1080p \
--aspect-ratio 16:9
Run b-roll layout QC:
python3 tools/broll_layout_qc.py tmp/video_jobs/my_job/assets/*.mp4 --job-dir tmp/video_jobs/my_job
Run final technical QC:
python3 tools/ffmpeg_qc.py tmp/video_jobs/my_job/final/master.mp4
The skill strongly avoids generic "AI slop." A good visual answers:
What state change should the viewer understand at this sentence?
Good visual choices:
Bad visual choices:
Every serious video should pass:
broll_layout_qc.py confirms no PiP/caption collisions.ffmpeg_qc.py confirms stream, duration, codec, audio, resolution, and black-frame checks.Use remotion-template/ when you want a React-based editor/timeline:
cd remotion-template
npm install
npm run dev
Render:
npx remotion render src/index.ts CaptionedTalkingHead out/video.mp4
Use hyperframes-template/ when you want HTML-native timeline composition:
cd hyperframes-template
npm install
npm run dev
Use the super-video-maker skill.
Goal: create a polished Avatar Explainer.
Length: 90 seconds.
Format: 16:9.
Presenter: HeyGen avatar.
Style: source receipts, UI micro-stories, fast editorial pacing, centered captions.
Before paid calls:
- show the source deck,
- show the script,
- show the storyboard,
- list the paid generation calls and cost drivers.
After generation:
- transcribe the audio,
- align visuals to Whisper timestamps,
- run b-roll layout QC,
- run final FFmpeg QC,
- sample frames and visually inspect the result.
video_orchestrator.py recipe runner for avatar-explainer.Distribb helps founders and operators build SEO systems: keyword research, original data research, content publishing, internal linking, backlinks, and content repurposing.
Learn more at distribb.io.
13 commits
Python
81.9%
TypeScript
17.6%
AI video production skill for agents: HeyGen avatars, Seedance b-roll, OpenAI images, Remotion, HyperFrames, screen recording, FFmpeg captions and QC.
272
stars
13
commits
Python
primary language
Aug 9, 2026
updated
Built by the team at Distribb — the SEO and growth autopilot for operators.
→ Build and scale content systems with us at distribb.io.
An end-to-end AI video production skill for agentic coding frameworks. Give your Cursor, Claude Code, or other shell-capable AI agent a video idea, source link, product flow, screen recording, or script, and this skill teaches the agent how to turn it into a polished video using HeyGen avatars, screen recordings, AI b-roll, OpenAI image generation, Remotion, HyperFrames, FFmpeg, captions, music, and quality-control loops.
This repo is designed to be dropped into an AI agent project as a reusable skill. It includes the actual instruction file (SKILL.md), deep production references, workflow examples, FFmpeg recipes, Python tools, and starter Remotion/HyperFrames templates.
The flagship format is:
Avatar Explainers (avatar-explainer) — proof-driven videos with a synthetic presenter, source receipts, screen recordings, UI micro-stories, captions, and action takeaways.
Most AI video tools stop at one layer:
Real videos need the whole pipeline:
This skill gives an AI agent the operating system for that process.
super-video-maker-skill/
├── SKILL.md # Main agent instructions
├── REFERENCE.md # Provider choices, design logic, quality gates
├── WORKFLOW_EXAMPLES.md # Full recipes, including Avatar Explainers
├── FFMPEG_PLAYBOOK.md # Practical FFmpeg recipes
├── REMOTION_VIDEO_GUIDE.md # Remotion production style guide
├── requirements.txt # Python dependencies
├── package.json # Root JS tooling dependencies
├── .env.example # Environment variable template
├── tools/
│ ├── heygen_client.py # HeyGen avatar generation + polling + download
│ ├── replicate_video.py # Seedance 2.0 via Replicate (legacy fallback)
│ ├── image_provider.py # OpenAI image generation/editing helper
│ ├── screen_recorder.py # FFmpeg/Xvfb or Playwright screen recording
│ ├── agent_browser_recorder.py # Agent-operated browser proof recording
│ ├── demo_video_composer.py # Polished product demo composer
│ ├── video_captioner.py # Whisper + ASS captions + shorts rendering
│ ├── music_provider.py # ElevenLabs music helper
│ ├── local_explainer_broll.py # Local fallback b-roll renderer
│ ├── broll_layout_qc.py # Visual layout QC contact sheets
│ └── ffmpeg_qc.py # Final technical QC
├── remotion-template/ # Starter Remotion project
└── hyperframes-template/ # Starter HyperFrames/HTML timeline
Clone the repo:
git clone https://github.com/Bomx/super-video-maker-skill.git
cd super-video-maker-skill
Install Python dependencies:
python3 -m venv venv
source venv/bin/activate
pip3 install -r requirements.txt
python3 -m playwright install chromium
Install JavaScript dependencies if you want Remotion or HyperFrames:
npm install
cd remotion-template && npm install && cd ..
cd hyperframes-template && npm install && cd ..
Install system dependencies:
brew install ffmpeg
On Linux servers you may also need:
sudo apt-get update
sudo apt-get install -y ffmpeg xvfb
Create your environment file:
cp .env.example .env
Then fill in the keys you plan to use.
Minimum useful setup:
HEYGEN_API_KEY=
HEYGEN_AVATAR_ID=
HEYGEN_VOICE_ID=
OPENAI_API_KEY=
REPLICATE_API_TOKEN=
ELEVENLABS_API_KEY=
Optional:
AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=
AWS_REGION=us-east-1
AWS_S3_BUCKET=
SOUNDTRACKS_S3_BASE_URL=
ANTHROPIC_API_KEY=
Provider notes:
HEYGEN_AVATAR_ID and HEYGEN_VOICE_ID are separate values.Never commit .env, cookies, generated videos, recordings, or user sessions.
Copy the folder into your project:
mkdir -p .agents/skills
cp -R super-video-maker-skill .agents/skills/super-video-maker
Then ask your agent:
Use the super-video-maker skill to create an avatar explainer about this topic...
Place SKILL.md and the supporting files wherever your framework loads skills or system prompts from. The important part is that the agent can read:
SKILL.md,REFERENCE.md,WORKFLOW_EXAMPLES.md,FFMPEG_PLAYBOOK.md,REMOTION_VIDEO_GUIDE.md,tools/ directory.If your framework does not support skills natively, paste SKILL.md into the agent's system prompt and keep the rest of the files in the working directory.
Example prompt to your agent:
Use the super-video-maker skill.
Make a 90-second Avatar Explainer about a trending SEO topic.
Use a recent X.com post as a trend signal, but verify the claims with official sources.
Use my HeyGen avatar.
Use screen/source receipts and UI micro-stories.
Do not make generic AI b-roll.
Pause before paid HeyGen/OpenAI/Replicate calls and show me the plan first.
Expected agent flow:
broll_layout_qc.py.ffmpeg_qc.py.Use avatar-explainer when the video combines:
The default structure:
Hook
→ casual avatar disclosure
→ news/update beat
→ concrete example
→ source proof
→ action steps
→ spoken CTA tail over outro card
Important rules:
Generate a HeyGen avatar clip:
python3 tools/heygen_client.py \
--script-file script.txt \
--output tmp/video_jobs/my_job/avatar.mp4 \
--avatar-id "$HEYGEN_AVATAR_ID" \
--voice-id "$HEYGEN_VOICE_ID"
Generate Seedance b-roll:
python3 tools/replicate_video.py generate \
--prompt "documentary-style browser research shot, source receipt, modern editorial pacing" \
--duration 7 \
--resolution 1080p \
--aspect-ratio 16:9
Run b-roll layout QC:
python3 tools/broll_layout_qc.py tmp/video_jobs/my_job/assets/*.mp4 --job-dir tmp/video_jobs/my_job
Run final technical QC:
python3 tools/ffmpeg_qc.py tmp/video_jobs/my_job/final/master.mp4
The skill strongly avoids generic "AI slop." A good visual answers:
What state change should the viewer understand at this sentence?
Good visual choices:
Bad visual choices:
Every serious video should pass:
broll_layout_qc.py confirms no PiP/caption collisions.ffmpeg_qc.py confirms stream, duration, codec, audio, resolution, and black-frame checks.Use remotion-template/ when you want a React-based editor/timeline:
cd remotion-template
npm install
npm run dev
Render:
npx remotion render src/index.ts CaptionedTalkingHead out/video.mp4
Use hyperframes-template/ when you want HTML-native timeline composition:
cd hyperframes-template
npm install
npm run dev
Use the super-video-maker skill.
Goal: create a polished Avatar Explainer.
Length: 90 seconds.
Format: 16:9.
Presenter: HeyGen avatar.
Style: source receipts, UI micro-stories, fast editorial pacing, centered captions.
Before paid calls:
- show the source deck,
- show the script,
- show the storyboard,
- list the paid generation calls and cost drivers.
After generation:
- transcribe the audio,
- align visuals to Whisper timestamps,
- run b-roll layout QC,
- run final FFmpeg QC,
- sample frames and visually inspect the result.
video_orchestrator.py recipe runner for avatar-explainer.Distribb helps founders and operators build SEO systems: keyword research, original data research, content publishing, internal linking, backlinks, and content repurposing.
Learn more at distribb.io.
13 commits
Python
81.9%
TypeScript
17.6%