According to AlphaMoat, as of 2026-09, Video Messages from your openclaw has 4,479 downloads and 5 stars — ranked #2,157 of 5,078 AI skills overall, and #210 of 512 in Design & Media.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 141 | 4.3K | 4 | - |
| SkillHub ↗ | 576 | 4.5K | 5 | — |
Platforms count differently and update at different times.
It turns text or audio into an avatar video with lip sync, synthesising speech first when the input is text and then rendering an MP4 through avatarcam. Output can be shaped as a Telegram circular video note. Avatar and background come from TOOLS.md. On Linux without a display it runs under a virtual display, and it depends on ffmpeg and avatarcam. Review the npm package identity before installing. Generated media and avatar/background assets may be sent through Telegram; use that path only when sharing is intended. Replace broad temporary-file cleanup with deletion of the exact output for the current run.
Profile published 2026-10-27
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 4.5K | — | 5 |
| 2026-08 | 4.2K | +4.5% | 5 |
| 2026-07 | 4.0K | +7.8% | 5 |
| 2026-06 | 3.7K | +1.1% | 4 |
| 2026-05 | 3.7K | — | 5 |
| 2026-03 | 3.4K | — | 4 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
---
name: video-message
description: Generate and send video messages with a lip-syncing VRM avatar. Use when user asks for video message, avatar video, video reply, or when TTS should be delivered as video instead of audio.
metadata:
{
"openclaw":
{
"emoji": "🎥",
"requires": { "bins": ["ffmpeg", "avatarcam"] },
"install": [
{
"id": "npm",
"kind": "npm",
"package": "@thewulf7/openclaw-avatarcam",
"global": true,
"bins": ["avatarcam"],
"label": "Install avatarcam (npm)",
},
{
"id": "brew",
"kind": "brew",
"formula": "ffmpeg",
"bins": ["ffmpeg"],
"label": "Install ffmpeg (brew)",
},
{
"id": "apt",
"kind": "apt",
"packages": ["xvfb", "xauth"],
"label": "Install headless X dependencies (Linux only)",
},
],
},
}
---
# Video Message
Generate avatar video messages from text or audio. Outputs as Telegram video notes (circular format).
## Installation
```bash
npm install -g openclaw-avatarcam
```
## Configuration
Configure in `TOOLS.md`:
```markdown
### Video Message (avatarcam)
- avatar: default.vrm
- background: #00FF00
```
### Settings Reference
| Setting | Default | Description |
|---------|---------|-------------|
| `avatar` | `default.vrm` | VRM avatar file path |
| `background` | `#00FF00` | Color (hex) or image path |
## Prerequisites
### System Dependencies
| Platform | Command |
|----------|---------|
| **macOS** | `brew install ffmpeg` |
| **Linux** | `sudo apt-get install -y xvfb xauth ffmpeg` |
| **Windows** | Install ffmpeg and add to PATH |
| **Docker** | See Docker section below |
> **Note:** macOS and Windows don't need xvfb — they have native display support.
### Docker Users
Add to `OPENCLAW_DOCKER_APT_PACKAGES`:
```
build-essential procps curl file git ca-certificates xvfb xauth libgbm1 libxss1 libatk1.0-0 libatk-bridge2.0-0 libgdk-pixbuf2.0-0 libgtk-3-0 libasound2 libnss3 ffmpeg
```
## Usage
```bash
# With color background
avatarcam --audio voice.mp3 --output video.mp4 --background "#00FF00"
# With image background
avatarcam --audio voice.mp3 --output video.mp4 --background "./bg.png"
# With custom avatar
avatarcam --audio voice.mp3 --output video.mp4 --avatar "./custom.vrm"
```
## Sending as Video Note
Use OpenClaw's `message` tool with `asVideoNote`:
```
message action=send filePath=/tmp/video.mp4 asVideoNote=true
```
## Workflow
1. **Read config** from TOOLS.md (avatar, background)
2. **Generate TTS** if given text: `tts text="..."` → audio path
3. **Run avatarcam** with audio + settings → MP4 output
4. **Send as video note** via `message action=send filePath=... asVideoNote=true`
5. **Return NO_REPLY** after sending
## Example Flow
User: "Send me a video message saying hello"
```bash
# 1. TTS
tts text="Hello! How are you today?" → /tmp/voice.mp3
# 2. Generate video
avatarcam --audio /tmp/voice.mp3 --output /tmp/video.mp4 --background "#00FF00"
# 3. Send as video note
message action=send filePath=/tmp/video.mp4 asVideoNote=true
# 4. Reply
NO_REPLY
```
## Technical Details
| Setting | Value |
|---------|-------|
| Resolution | 384x384 (square) |
| Frame rate | 30fps constant |
| Max duration | 60 seconds |
| Video codec | H.264 (libx264) |
| Audio codec | AAC |
| Quality | CRF 18 (high quality) |
| Container | MP4 |
### Processing Pipeline
1. Electron renders VRM avatar with lip sync at 1280x720
2. WebM captured via `canvas.captureStream(30)`
3. FFmpeg processes: crop → fps normalize → scale → encode
4. Message tool sends via Telegram `sendVideoNote` API
## Platform Support
| Platform | Display | Notes |
|----------|---------|-------|
| macOS | Native Quartz | No extra deps |
| Linux | xvfb (headless) | `apt install xvfb` |
| Windows | Native | No extra deps |
## Headless Rendering
Avatarcam auto-detects headless environments:
- Uses `xvfb-run` when `$DISPLAY` is not set (Linux only)
- macOS/Windows use native display
- GPU stall warnings are safe to ignore
- Generation time: ~1.5x realtime (20s audio ≈ 30s processing)
## Notes
- Config is read from TOOLS.md
- Clean up temp files after sending: `rm /tmp/video*.mp4`
- For regular video (not circular), omit `asVideoNote=true`
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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.