talking-avatar

talking-avatar is a skill for Codex from buildfastwithai/gen-ai-experiments. It costs 96 tokens per session (1,457 once invoked), scanned A, original, MIT.

A tool for building a voice-chat app with one talking character whose mouth animation follows the other person’s audio. The character can come from a supplied photo or a text description.

In plain words
What is it for?
Use it to create a talking avatar, voice character chatbot, roleplaying companion, or reusable realtime voice interface.
Why use it?
It provides a defined way to turn a character image into a voice conversation with matching mouth movements.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: mentions Codex.

Good fit Use it to create a talking avatar, voice character chatbot, roleplaying companion, or reusable realtime voice interface.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/buildfastwithai/gen-ai-experiments/talking-avatar
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add buildfastwithai/gen-ai-experiments --skill talking-avatar
Clone the repo
git clone --depth 1 https://github.com/buildfastwithai/gen-ai-experiments

Made for: Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for talking-avatar

README.md
[![agentmods](https://agentmods.dev/badge/skills/buildfastwithai/gen-ai-experiments/talking-avatar/github.svg)](https://agentmods.dev/skills/buildfastwithai/gen-ai-experiments/talking-avatar)
Your own site
<a href="https://agentmods.dev/skills/buildfastwithai/gen-ai-experiments/talking-avatar"><img src="https://agentmods.dev/badge/skills/buildfastwithai/gen-ai-experiments/talking-avatar/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

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Your own site · 80×15
<a href="https://agentmods.dev/skills/buildfastwithai/gen-ai-experiments/talking-avatar"><img src="https://agentmods.dev/badge/skills/buildfastwithai/gen-ai-experiments/talking-avatar.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 96 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,457 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00096 $0.01457
Opus 5.5 $0.00038 $0.00583
Sonnet 5.5 $0.00019 $0.00291
Haiku 4.5 $0.00010 $0.00146

Measured 1mo ago against content hash 45d581446690, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

talking-avatar scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/scaffold_app.py, scripts/validate_avatar_assets.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/talking-avatar/SKILL.md · 101 lines

How it starts

The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Talking Avatar

Create one focused voice conversation with a fixed character portrait whose mouth poses follow the actual remote audio. Accept either a photograph or a character description, generate a canonical portrait plus small mouth sprites, and build the app around OpenAI Realtime.

Coordinate the required skills

  • Use imagegen for every canonical portrait or mouth-frame generation/edit. Read its full instructions before generating.
  • Use openai-docs and, when applicable, openai-platform-api-key to verify the current Realtime WebRTC endpoint, session schema, model, voices, and credential flow. Never rely on this skill's model examples as current truth.
  • Use the available frontend design skill for interface work.
  • If .openai/hosting.json exists, follow sites-building and sites-hosting through deployment.
  • Do not add backgrounds, wardrobes, role modes, or multiple characters unless the user explicitly asks. The default product is one avatar and one conversation.

Choose the input path

  1. Photograph supplied: inspect it with view_image, treat it as an identity reference, and preserve face shape, skin tone, hair, glasses, facial hair, and distinguishing features.
  2. Character described: normalize the description into a concrete visual spec. Ask only for a missing detail that materially changes identity, such as photorealistic versus illustrated. Otherwise proceed with tasteful defaults.
  3. Establish the character name, concise persona, app name, language, and preferred voice. Infer reasonable defaults when safe.

Read references/image-pipeline.md before creating or editing the avatar assets.

Build the asset set

  1. Generate one canonical, front-facing, evenly lit, closed-mouth portrait. Lock its canvas, crop, head position, gaze, pose, clothing, background, and lighting.
  2. From that canonical image, generate three separate identity-preserving edits:
    • soft: lips slightly parted;
    • round: a natural rounded vowel;
    • open: a natural medium-open vowel.
  3. Repeat the invariants in every edit prompt. Change only the immediate lips and inner mouth. Reject frames with moved eyes, jaw, glasses, head, beard, clothing, or lighting.
  4. Crop the smallest practical identical rectangle from all three speech frames. Keep enough surrounding skin for feathering, but do not ship full-frame speech images.
  5. Save exactly these project assets by default:
    • public/avatar/avatar-base.jpg
    • public/avatar/mouth-soft.png
    • public/avatar/mouth-round.png
    • public/avatar/mouth-open.png
  6. Run scripts/validate_avatar_assets.py --dir <project>/public/avatar and fix all failures.

Read the full file on GitHub · 101 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 101 lines · 96 tokens per session scan A 45d581446690

Subscribe to this mod's changes

talking-avatar is a skill published in the GitHub repository buildfastwithai/gen-ai-experiments (789 stars, last pushed 1mo ago), licensed MIT. It adds 96 tokens to every session and 1,457 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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