Skills ai-avatar-video
๐Ÿ“ฆ

ai-avatar-video

Content revision r2 High Risk โš™๏ธ External commands๐ŸŒ Network access

Create AI Avatar and Talking-Head Videos

Producing presenter videos requires coordinated portrait, speech, and lip-sync tools. This skill guides inference.sh model selection and belt CLI workflows.

Supports: Claude Codex Code(CC)
โš ๏ธ 38 Poor

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request
Review the Skillstore skill "ai-avatar-video" from https://skillstore.io/skills/skills-shell-ai-avatar-video.md and its manifest at https://skillstore.io/api/skills/skills-shell-ai-avatar-video/manifest. Verify the artifact. Stop and obtain explicit user consent before installing or changing files.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Test it

Using "ai-avatar-video". Create a product walkthrough from my approved portrait and 30-second script.

Expected outcome:

  • Recommended model: P-Video-Avatar with built-in speech.
  • Planned output: 720p talking-head video using the supplied portrait and script.
  • Approval needed before uploading media or starting the paid inference job.

Using "ai-avatar-video". Which model should animate two people from one image?

Expected outcome:

OmniHuman 1.5 is the documented multi-character option. Provide approved image and audio sources, then confirm before submitting the hosted job.

Using "ai-avatar-video". Plan a Spanish dub for an existing training video.

Expected outcome:

  • Transcribe the approved source video.
  • Review the Spanish translation before speech generation.
  • Generate approved Spanish speech and lip-sync it to the original video.
  • Review timing, pronunciation, consent, and disclosure before distribution.

Security Audit

High Risk
v5 โ€ข 9/7/2026 Open versioned report

The skill legitimately invokes hosted inference models, so command blocks that run belt, redirect outputs, loop over jobs, or install packages are confirmed. Formatting-only backticks and placeholder or documentation URLs are false positives, while the remote image carries a minor privacy risk. The UGC workflow also encourages synthetic testimonials designed to appear authentic.

1
Files scanned
268
Lines analyzed
16
Review items
0
False positives ignored

Confirmed security concerns (1)

High
Deceptive Synthetic Testimonial Workflow
The UGC workflow generates fictional speakers who claim product experience, describes them as authentic testimonials, and demonstrates producing multiple presenters at scale.
The example script claims personal product use, while the prompts explicitly request an authentic testimonial from generated presenters.
Capability review items (16)

These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.

Medium
Ruby/shell backtick execution
> **Install the belt CLI skill:** `npx skills add belt-sh/cli`
Line 7 instructs users to run npx against a remote package, which can download and execute package code.
Medium
Ruby/shell backtick execution
```bash
This range contains belt login and a hosted model invocation, both of which execute an external CLI and can create network activity or charges.
Medium
Ruby/shell backtick execution
```bash
The code block runs belt against a hosted avatar model, causing an external process and remote inference request.
Medium
Ruby/shell backtick execution
```bash
The range runs belt against a hosted avatar model with user-selected media and style inputs.
Medium
Ruby/shell backtick execution
```bash
The code block invokes belt and sends image and audio references to a hosted model.
Medium
Ruby/shell backtick execution
```bash
The range contains two belt model invocations that generate an image and then an avatar video.
Medium
Ruby/shell backtick execution
```bash
The code block invokes belt to submit image and audio inputs to the OmniHuman service.
Medium
Ruby/shell backtick execution
```bash
The code block executes belt to send image and audio inputs to a hosted Fabric model.
Medium
Ruby/shell backtick execution
```bash
The code block executes belt to submit media to the hosted PixVerse lipsync model.
Medium
Ruby/shell backtick execution
```bash
The range invokes two hosted models and redirects command output into speech.json, creating both network and filesystem effects.
Medium
Ruby/shell backtick execution
```bash
The dubbing workflow invokes three hosted models and redirects results into local files.
Medium
Ruby/shell backtick execution
```bash
The block executes two belt jobs to generate a portrait and synthetic presenter video.
Medium
Ruby/shell backtick execution
```bash
The shell loop runs three hosted inference jobs and interpolates the voice variable, creating repeated billable external actions.
Medium
Ruby/shell backtick execution
```bash
The code block contains five npx installation commands that can fetch and execute remote package code.
Medium
Ruby/shell backtick execution
```
Although line 259 closes a block, this finding range also includes an inline belt command that lists remote video applications.
Low
Hardcoded URL
![AI Avatar & Talking Head Videos](https://cloud.inference.sh/app/files/u/4mg21r6ta37mpaz6ktzwtt8krr
The Markdown embeds a remote image, so rendering the document can contact cloud.inference.sh and disclose viewer network metadata.
Audited by: codex View Audit History โ†’
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Open versioned report
Security Assessment

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Academic citations (APA ยท BibTeX ยท CFF)

APA citation

skills-shell. (2026). ai-avatar-video security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/skills-shell-ai-avatar-video/audits/5

BibTeX citation

@techreport{skills-shell-skills-shell-ai-avatar-video-2026, author = {skills-shell}, title = {ai-avatar-video security audit report (audit version 5)}, institution = {Skillstore}, year = {2026}, number = {5}, url = {https://skillstore.io/skills/skills-shell-ai-avatar-video/audits/5}, note = {Author version unspecified} }

CITATION.cff

cff-version: 1.2.0 message: "If you use this Skill, cite its author and this versioned security audit report." title: "ai-avatar-video security audit report (audit version 5)" version: "unspecified" type: report authors: - name: "skills-shell" date-released: "2026-09-07" url: "https://skillstore.io/skills/skills-shell-ai-avatar-video/audits/5" identifiers: - type: other value: "skillstore:skills-shell-ai-avatar-video:audit:5" description: "Skillstore immutable audit report identifier"

Compare variants

11 installable variants

Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.

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Evidence Confidence High
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Evidence Confidence Medium
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Evidence Confidence Medium
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Skillstore Score

Why this score Evidence Confidence: Medium
55
Architecture
85
Maintainability
87
Content
67
Community
83
Spec Compliance

What You Can Build

Produce Course Presenters

Turn approved instructor portraits and lesson scripts into consistent talking-head segments.

Localize Existing Videos

Transcribe, translate, synthesize speech, and lip-sync approved videos for another language.

Create Character Dialogue

Generate voiced avatar clips for original game characters and approved virtual presenters.

Try These Prompts

Create a Basic Avatar
Create a 720p talking-head video from my approved portrait. Use this script: [script]. Ask before running any paid command.
Choose an Avatar Model
Compare P-Video-Avatar, OmniHuman, Fabric, and PixVerse for [requirements]. Recommend one model and explain cost, speed, inputs, and limitations.
Build a Dubbing Workflow
Plan a consented dubbing workflow for [video] from [source language] to [target language]. Confirm each external job before execution.
Design a Reviewed Batch Pipeline
Design a batch workflow for [number] approved presenters. Estimate jobs and costs, require disclosure, validate inputs, and pause before all external commands.

Best Practices

  • Use front-facing, well-lit portraits and clean audio from consenting participants.
  • Estimate service costs and obtain approval before every hosted or batch job.
  • Review lip sync, pronunciation, factual claims, rights, and synthetic-media disclosures before publishing.

Avoid

  • Do not imitate a real person without explicit authorization.
  • Do not present generated endorsements as genuine customer experiences.
  • Do not execute remote installers or paid inference jobs without informed approval.

Frequently Asked Questions

Which model supports scripts without separate audio?
P-Video-Avatar includes text-to-speech and accepts a portrait with a voice script.
Which model supports multiple people?
The skill identifies OmniHuman 1.5 for multi-character, audio-driven animation.
Can this skill dub an existing video?
Yes. It outlines transcription, translation, speech generation, and LatentSync lip-sync stages.
Does the skill work without network access?
No. The belt CLI calls hosted inference services and requires authentication.
Will video generation create charges?
It may. Review current provider pricing and confirm estimated usage before starting each job.
Can I use any portrait or voice?
Only use media you own or are authorized to process. Obtain consent and disclose synthetic output where required.

Developer Details

License

MIT

Skillstore revision

r2

Version notice

The author did not declare a version.

Ref

b1ef80115e869b66867d4eac8e3c8dc56a393a8d

Maintenance freshness

9/7/2026

Usage

24 downloads ยท 0 views

File structure

๐Ÿ“„ SKILL.md

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