Skills ai-avatar-video
📦
ai-avatar-video
Content revision r1 High Risk ⚙️ External commands🌐 Network access
Create AI Avatar and Talking Head Videos
Avatar video production often requires separate speech, animation, and lip-sync tools. This skill organizes inference.sh models into reusable presenter, dubbing, and UGC workflows.
Supports: Claude Codex Code(CC)
Stop for confirmation before installing.
Review the plan and obtain explicit user consent before changing files.
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/101-skills-ai-avatar-video.md and its manifest at https://skillstore.io/api/skills/101-skills-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 neutral 720p presenter video from an authorized portrait and a 30-second onboarding script.
Expected outcome:
- Selected P-Video-Avatar for integrated speech and portrait animation.
- Prepared a neutral English voice and 720p output.
- Submitted the approved portrait and onboarding script for generation.
Using "ai-avatar-video". Dub an existing safety training video into Spanish using an approved replacement voice.
Expected outcome:
- Transcribed the source narration.
- Prepared a Spanish translation for review.
- Generated approved Spanish speech and synchronized it with the source video.
Using "ai-avatar-video". Create three disclosed vertical presenter variants for a product campaign.
Expected outcome:
- Prepared three authorized presenter and voice combinations.
- Applied consistent campaign messaging and vertical framing.
- Submitted three 1080p variants for generation.
Security Audit
High Riskv5 • 7/12/2026 Open versioned report
Most detections are Markdown backticks, code fences, placeholder media URLs, or documentation links rather than executable backticks or suspicious destinations. Real risks remain in third-party package installation, remote media processing, shell command construction, remote image loading, and synthetic testimonial workflows without consent safeguards.
1
Files scanned
268
Lines analyzed
16
Review items
0
False positives ignored
Confirmed security concerns (3)
High
Shell Injection Through Inline JSON Inputs
User-controlled scripts and media values are placed inside shell-quoted JSON. Quotes or shell substitutions can alter commands when an agent inserts input without structured serialization.
The examples directly embed text in single-quoted and double-quoted shell arguments without a JSON serializer. Generated scripts can contain quote or substitution characters.
High
Deceptive Synthetic Testimonial Risk
The skill generates testimonial-style UGC and multiple presenters without requiring likeness consent or synthetic-media disclosure. This can facilitate deceptive endorsements or impersonation.
The examples explicitly create product testimonials and several presenters, while the guidance contains no consent, disclosure, or impersonation restrictions.
Medium
External Processing of Potentially Sensitive Media
The workflows send portraits, voice scripts, audio, and videos to remote inference applications. The skill provides no consent, retention, pricing, or privacy warning.
Multiple belt app run examples submit media URLs and scripts to named remote models. No data-handling notice appears in the skill.
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`
The line explicitly directs users to execute npx against a third-party package source. This performs package resolution and installation without a pinned version.
Medium
Ruby/shell backtick execution
```bash
The fenced example instructs execution of belt login and a remote model invocation. These are intentional external commands that authenticate and submit media generation inputs.
Medium
Ruby/shell backtick execution
```bash
The fenced block directs execution of belt app run with portrait and speech inputs. This is genuine external command usage for remote video generation.
Medium
Ruby/shell backtick execution
```bash
The fenced block instructs belt to invoke a remote avatar model with style and speech inputs. This is intended external command execution.
Medium
Ruby/shell backtick execution
```bash
The example executes belt app run and submits portrait and audio references to a remote model. It is real external command usage.
Medium
Ruby/shell backtick execution
```bash
The workflow runs two belt model commands to generate a portrait and avatar video. These are genuine remote command invocations.
Medium
Ruby/shell backtick execution
```bash
The block invokes the OmniHuman application through belt with image and audio references. This is intentional external command execution.
Medium
Ruby/shell backtick execution
```bash
The example invokes the Fabric application through belt using image and audio inputs. It is real external command execution.
Medium
Ruby/shell backtick execution
```bash
The fenced block runs the PixVerse lip-sync model through belt. This is genuine external command execution against a remote service.
Medium
Ruby/shell backtick execution
```bash
The workflow executes text-to-speech and avatar applications through belt and redirects output to a local file. These are real shell operations.
Medium
Ruby/shell backtick execution
```bash
The dubbing workflow runs transcription, speech, and lip-sync applications and redirects two outputs to files. These are genuine external and filesystem-affecting commands.
Medium
Ruby/shell backtick execution
```bash
The UGC workflow executes image and avatar generation applications through belt. These are intentional remote commands using generated content inputs.
Medium
Ruby/shell backtick execution
```bash
The block uses a shell loop, variable expansion, and repeated belt invocations. This is genuine shell execution, although the documented voice list is fixed.
Medium
Ruby/shell backtick execution
```bash
The block recommends several npx package installation commands from external repositories without pinned revisions. Executing them introduces package supply-chain risk.
Low
Hardcoded URL
. [Install instructions](https://raw.githubusercontent.com/infer
The install link loads raw instructions from a mutable main branch on GitHub. Following mutable remote guidance creates a limited supply-chain and content-change risk.
Risk Factors
⚙️ External commands (33)
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Audited by: codex View Audit History →
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APA citation
101-skills. (2026). ai-avatar-video security audit report (audit version 5) [Author version unspecified]. Skillstore. https://skillstore.io/skills/101-skills-ai-avatar-video/audits/5BibTeX citation
@techreport{101-skills-101-skills-ai-avatar-video-2026,
author = {101-skills},
title = {ai-avatar-video security audit report (audit version 5)},
institution = {Skillstore},
year = {2026},
number = {5},
url = {https://skillstore.io/skills/101-skills-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: "101-skills"
date-released: "2026-07-12"
url: "https://skillstore.io/skills/101-skills-ai-avatar-video/audits/5"
identifiers:
- type: other
value: "skillstore:101-skills-ai-avatar-video:audit:5"
description: "Skillstore immutable audit report identifier"
Compare variants
11 installable variantsEach author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
Higher Skillstore usage
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Skillstore Score 69
Evidence Confidence High
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Skillstore Score 50
Evidence Confidence High
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Skillstore Score 50
Evidence Confidence High
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qu-skills-ai-avatar-video
Skillstore Score 50
Evidence Confidence Medium
Skillstore usage 9
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agentspace-so-ai-avatar-video
Skillstore Score 38
Evidence Confidence High
Skillstore usage 7
Updated
2026-08-21
doany-ai-ai-avatar-video
Skillstore Score 38
Evidence Confidence Medium
Skillstore usage 10
Updated
2026-08-21
inference-sh-ai-avatar-video
Skillstore Score 38
Evidence Confidence Medium
Skillstore usage 9
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101-skills Current
101-skills-ai-avatar-video
Skillstore Score 38
Evidence Confidence Medium
Skillstore usage 6
Updated
2026-08-21
Skillstore Score
Why this score Evidence Confidence: Medium 55
Architecture
85
Maintainability
87
Content
65
Community
83
Spec Compliance
What You Can Build
Produce product explainers
Turn an approved presenter portrait and concise script into a narrated product walkthrough.
Localize training videos
Transcribe a training video, translate its narration, generate speech, and synchronize the new audio.
Create character dialogue
Animate an authorized character image with expressive speech for game scenes or interactive prototypes.
Try These Prompts
Create a basic presenter
Create a 720p talking-head video from [portrait URL]. Use this script: [script]. Choose a clear, neutral English voice.
Direct voice and scene
Create a 1080p presenter video from [portrait URL] and [script]. Use an enthusiastic voice and describe a professional studio setting.
Build a dubbing workflow
Dub [video URL] into [language]. Transcribe, translate, generate approved speech, and synchronize it while preserving the original visual timing.
Generate approved presenter variants
Create three disclosed synthetic presenter variants for [campaign]. Use authorized portraits, distinct voices, consistent messaging, and vertical 1080p output.
Best Practices
- Use front-facing, well-lit portraits and clean audio for stable facial animation.
- Confirm likeness, voice, script, and media rights before sending inputs to remote models.
- Review generated speech, lip synchronization, claims, and disclosure labels before publication.
Avoid
- Do not animate a real person without documented permission.
- Do not embed unescaped user text directly inside shell-quoted input arguments.
- Do not publish synthetic testimonials as genuine customer endorsements.
Frequently Asked Questions
Which model should I try first?
The skill recommends P-Video-Avatar for integrated speech, style controls, and 720p or 1080p output.
Can I use recorded audio instead of text?
Yes. P-Video-Avatar and the listed lip-sync models accept audio URLs with compatible portrait inputs.
Can this skill dub an existing video?
Yes. The documented workflow combines transcription, translation, speech generation, and LatentSync.
Does the skill work without inference.sh?
No. It relies on the belt CLI, an authenticated account, and remotely hosted inference applications.
Does it guarantee model pricing or speed?
No. The document includes estimates, but providers can change prices, performance, availability, and limits.
What permissions are required for avatar media?
Obtain explicit rights for every likeness, voice, script, and source video. Add clear synthetic-media disclosures where required.
Developer Details
Author
101-skillsLicense
MIT
Skillstore revision
r1
Version notice
The author did not declare a version.
Ref
d71c7417a35d5c2624161bd2fe8de8a41a362128
Maintenance freshness
7/18/2026
Usage
2 downloads · 0 views
File structure
📄 SKILL.md