复制安装命令
用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。
复制前请先查看来源、License 和安全提示。
This is the open-source content repository behind
用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。
复制前请先查看来源、License 和安全提示。
来源文件:README.md
This is the open-source content repository behind Skill Store. It stores every approved Agent Skill, the records that go with it, and the automated security audits published with each skill.
This repo is a companion to the Skill Store platform, not the place to submit skills. Skills are added through skillstore.io — its review pipeline writes to this repo automatically. Please do not open a pull request here to add a skill; PRs adding skills will be closed. See Contributing a skill below.
The recommended way to install any skill is the skillstore CLI — one command works for both Claude Code and Codex:
npx skillstore add author/skill-name
For example:
npx skillstore add aiskillstore/code-review
It downloads the skill and drops it into the right skills/ directory for your tool. Claude Code auto-discovers it; for Codex, restart the session.
Prefer to do it by hand, or installing via Claude Web? See the full Installation Guides for every method (CLI, manual, and ZIP upload) and the scope directories (~/.agents/skills/, .claude/skills/, ~/.claude/skills/, .codex/skills/, …).
Submit through the platform — not through a pull request:
SKILL.md.SKILL.md — the skill definition (required, per the Agent Skills spec)LICENSE (recommended)Every submission is scanned automatically before it can be published. The audit flags things like:
eval, exec, raw system commands)Security analysis is report-only: findings inform maintainers and users, but a risk result does not automatically block an otherwise approved skill from being published. See our Security Trust Center for the methodology, limitations, and risk-level definitions.
Live Security Passport example:
.
├── skills/ # Approved, published skills (one folder each, with SKILL.md)
├── pending/ # Submissions awaiting review
├── packages/
│ ├── cli/ # The `skillstore` CLI (npx skillstore add …)
│ └── skillstore/
├── schemas/ # JSON schemas for skill records
├── scripts/ # Maintenance & scoring scripts
└── .github/workflows/ # Submission, audit, and sync automation
The contents of this repo are maintained by Skill Store's automated pipeline. Manual changes are limited to maintainers.
The marketplace catalog is MIT-licensed. Individual skills carry their own licenses — check each skill's LICENSE file.
name: ai-avatar-video
description: "Create AI avatar and talking head videos via inference.sh CLI. Recommended: P-Video-Avatar (fastest, cheapest, built-in TTS). Also: OmniHuman, Fabric, PixVerse. Audio: Inworld TTS-2 (100+ languages, emotion steering for characters), ElevenLabs, Kokoro. Capabilities: audio-driven avatars, text-to-avatar, lipsync videos, talking head generation, virtual presenters, UGC content. Use for: AI presenters, explainer videos, virtual influencers, dubbing, marketing videos, UGC ads, gaming avatars, NPC dialogue. Triggers: ai avatar, talking head, lipsync, avatar video, virtual presenter, ai spokesperson, audio driven video, heygen alternative, synthesia alternative, talking avatar, lip sync, video avatar, ai presenter, digital human, ugc, ugc video, ugc ad, avatar ugc"
allowed-tools: Bash(belt *)Install the belt CLI skill:
npx skills add belt-sh/cli
Create AI avatars and talking head videos via inference.sh CLI.

Requires inference.sh CLI (
belt). Install instructions
belt login
# Recommended: P-Video-Avatar (fastest, cheapest, built-in TTS)
belt app run pruna/p-video-avatar --input '{
"image": "https://portrait.jpg",
"voice_script": "Hello, welcome to our product demo!",
"voice": "Zephyr (Female)"
}'
Start with P-Video-Avatar — it's 18x faster and 6x cheaper than alternatives, with built-in TTS, dynamic backgrounds, and 1080p support.
| Model | App ID | Best For | Built-in TTS |
|---|---|---|---|
| P-Video-Avatar | pruna/p-video-avatar | Best overall: speed, cost, quality, control | Yes (30 voices, 10 languages) |
| OmniHuman 1.5 | bytedance/omnihuman-1-5 | Multi-character, audio-driven | No |
| Fabric 1.0 | falai/fabric-1-0 | Image talks with lipsync | Yes |
| PixVerse Lipsync | falai/pixverse-lipsync | Highly realistic lipsync | No |
| Model | Speed (per sec of video) | Cost per second |
|---|---|---|
| P-Video-Avatar | ~1.83s/s | $0.025 |
| OmniHuman 1.5 | ~28s/s (15x slower) | $0.16 (6.4x more) |
| Fabric 1.0 | ~34s/s (18x slower) | $0.14 (5.6x more) |
Generate avatar from portrait + text script with built-in TTS:
belt app run pruna/p-video-avatar --input '{
"image": "https://portrait.jpg",
"voice_script": "Welcome to our product walkthrough. Today I will show you three key features.",
"voice": "Puck (Male)",
"voice_language": "English (US)",
"resolution": "720p"
}'
With custom style control:
belt app run pruna/p-video-avatar --input '{
"image": "https://portrait.jpg",
"voice_script": "This is exciting news!",
"voice": "Aoede (Female)",
"voice_prompt": "Enthusiastic and energetic tone",
"video_prompt": "The person is presenting on stage with dramatic lighting",
"resolution": "1080p"
}'
With audio file instead of TTS:
belt app run pruna/p-video-avatar --input '{
"image": "https://portrait.jpg",
"audio": "https://speech.mp3"
}'
Use Pruna P-Image to generate the portrait, then create the avatar:
# 1. Generate a portrait image
belt app run pruna/p-image --input '{
"prompt": "professional headshot portrait of a young woman, neutral background, looking at camera, studio lighting, photorealistic",
"aspect_ratio": "9:16"
}'
# 2. Create avatar video with built-in TTS
belt app run pruna/p-video-avatar --input '{
"image": "<image-url-from-step-1>",
"voice_script": "Hi there! Let me walk you through our latest features.",
"voice": "Zephyr (Female)"
}'
belt app run bytedance/omnihuman-1-5 --input '{
"image_url": "https://portrait.jpg",
"audio_url": "https://speech.mp3"
}'
Supports specifying which character to drive in multi-person images.
belt app run falai/fabric-1-0 --input '{
"image_url": "https://face.jpg",
"audio_url": "https://audio.mp3"
}'
belt app run falai/pixverse-lipsync --input '{
"image_url": "https://portrait.jpg",
"audio_url": "https://speech.mp3"
}'
For models without built-in TTS (OmniHuman, PixVerse), generate speech first:
# 1. Generate speech — Inworld TTS-2 for expressive character voices
belt app run inworld/text-to-speech-2 --input '{
"text": "[friendly] Welcome to our product demo! [excited] Let me show you three features that will change how you work.",
"voice_id": "Sarah",
"delivery_mode": "CREATIVE"
}' > speech.json
# 2. Create avatar video with the speech
belt app run bytedance/omnihuman-1-5 --input '{
"image_url": "https://presenter-photo.jpg",
"audio_url": "<audio-url-from-step-1>"
}'
Tip: For most use cases, P-Video-Avatar with built-in TTS is simpler — no separate audio step needed. Use this workflow only when you specifically need OmniHuman (multi-character) or PixVerse (realistic lipsync).
# 1. Transcribe original video
belt app run infsh/fast-whisper-large-v3 --input '{"audio_url": "https://video.mp4"}' > transcript.json
# 2. Translate text (manually or with an LLM)
# 3. Generate speech in new language
belt app run infsh/kokoro-tts --input '{"text": "<translated-text>"}' > new_speech.json
# 4. Lipsync the original video with new audio
belt app run infsh/latentsync-1-6 --input '{
"video_url": "https://original-video.mp4",
"audio_url": "<new-audio-url>"
}'
Create UGC-style content with P-Video-Avatar — built-in TTS, no separate audio step needed:
# 1. Generate a relatable UGC-style portrait
belt app run pruna/p-image --input '{
"prompt": "casual selfie-style photo of a young woman in a cozy room, natural lighting, looking at camera, warm smile, authentic feel",
"aspect_ratio": "9:16"
}'
# 2. Create UGC avatar video with built-in TTS
belt app run pruna/p-video-avatar --input '{
"image": "<image-url-from-step-1>",
"voice_script": "Okay so I just tried this product and honestly? It is a game changer. I was not expecting to love it this much but here we are!",
"voice": "Zephyr (Female)",
"voice_prompt": "Excited, casual, authentic tone like talking to a friend",
"video_prompt": "The person is talking casually to camera in their room, natural gestures",
"resolution": "1080p"
}'
# Generate 3 different presenters
for voice in "Zephyr (Female)" "Puck (Male)" "Aoede (Female)"; do
belt app run pruna/p-video-avatar --input "{
\"image\": \"https://portrait.jpg\",
\"voice_script\": \"This changed my morning routine completely. Five minutes and I am done.\",
\"voice\": \"$voice\",
\"voice_prompt\": \"Casual, authentic, like a real testimonial\",
\"video_prompt\": \"Person talking to camera in a bright kitchen\",
\"resolution\": \"1080p\"
}"
done
pruna/p-image using 9:16 aspect ratio for vertical videos# Dedicated P-Video-Avatar skill
npx skills add inference-sh/skills@p-video-avatar
# Full platform skill (all apps)
npx skills add inference-sh/skills@infsh-cli
# Text-to-speech (generate audio for non-TTS avatar models)
npx skills add inference-sh/skills@text-to-speech
# Speech-to-text (transcribe for dubbing)
npx skills add inference-sh/skills@speech-to-text
# Video generation
npx skills add inference-sh/skills@ai-video-generation
# Image generation (create avatar images)
npx skills add inference-sh/skills@ai-image-generation
Browse all video apps: belt app store --category video
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