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Audio Production

Community
AIEGOBOT
audio-production

Generate and integrate local sound effects and other audio. Use when asked to build, finish or improve a game, edit a video, animate a scene, or create an interactive application or website where sound contributes to the requested result, even if audio is not mentioned. Also use for explicit audio requests. Do not use for unrelated analysis, documentation or refactoring, intentional silence, or when suitable audio already exists.

Overview

PublisherAIEGOBOT
Repositoryagent-audio
Skill nameaudio-production
Stars
52
Forks
11
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by AIEGOBOT on GitHub. Read the source before you install it.

Installation

Install the Audio Production AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/AIEGOBOT/agent-audio/tree/main/skills/audio-production
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/AIEGOBOT/agent-audio.git /tmp/agent-audio
mkdir -p .claude/skills
cp -r /tmp/agent-audio/skills/audio-production .claude/skills/audio-production
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Audio Production in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Audio Production on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Audio Production is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Audio Production

Use Agent Audio as the local generation tool, and finish the requested work rather than leaving the user a separate audio-production task. The current installation uses Stable Audio 3 Medium. Small-SFX is a separate benchmark option, not a model selectable through this Skill's MCP workflow.

Decide and inspect

Do not wait for an explicit audio request when an intended audible event is missing from the requested deliverable. Appropriate cases include impacts, collisions, movement, UI feedback, transitions and environmental ambience. Music can be appropriate when the task calls for it; do not add a soundtrack merely because a generation tool is available.

Before generating, inspect the project for suitable audio assets, existing audio systems, timing, style and output conventions. Reuse suitable assets. Do not generate for documentation, analysis, cleanup or refactoring; where silence is intended; when sound would change rather than complete the user's design; or when the user has asked for no audio.

Autonomy and boundaries

Make routine decisions about sound, prompts, candidates and integration within the requested task. Do not introduce a mandatory sound-plan approval or ask the user to choose candidates before completing the work. Honor an explicit request for review or alternatives, and never override the user's scope.

This does not authorize bypassing host permissions, accepting model terms, accessing unrelated files, or paying for external services. If installation, credentials or new permissions are required, report the blocker and obtain the required authorization; do not silently install a different backend or use a cloud provider. No routine creative checkpoint is needed after authorized setup.

Prompt design

Use concrete acoustic descriptions: source/material, action, weight, texture, space and timing. Match the existing sonic style rather than requesting generic "epic" sound. For example, specify a dry, close metallic impact with a sharp transient and a short decay. Include "no voice" or "no music" in the positive prompt when appropriate.

The current tool rejects nonempty negative_prompt; put desired characteristics and exclusions in prompt. See prompt examples when useful. A request for a seamless loop does not establish that the generated file actually loops cleanly.

Generate within a bounded task

  1. Call audio_status when runtime readiness is unknown. File readiness is not a successful generation test. Inspect the selected backend and reported limits.
  2. Start with the shortest practical asset for the event. A roughly 3-second source is a useful starting point for a short effect, not a speed guarantee. The meaningful event may occupy only part of the generated file.
  3. Call generate_audio with prompt, seconds and, when useful, a new .wav output_path in the intended project asset directory. Omitting the path uses Agent Audio's output folder; move/copy and integrate the asset when required. Never overwrite existing outputs or assume a failed call produced a new file.
  4. Generate only the distinct assets the task needs. Reuse assets where appropriate; do not request large candidate batches by default. When another candidate is justified, change the acoustic direction deliberately. Stop repeated attempts on a persistent error and report the limitation.

The current interface is text-to-WAV. It does not expose audio editing, inpainting, continuation, loop construction or mixing as MCP operations. Use the project's existing tools for trimming, timing, fades or mixing when available and authorized. Do not invent tool parameters or install new editing software without the appropriate authorization. Long CPU requests can time out.

Integrate and verify the deliverable

When the larger request requires integration, generating a file is not the end of the task. Use the existing project tools and audio system:

  • In games, connect the asset to the intended event and check triggering, repetition, restart behavior and the project's existing volume/mute controls.
  • In videos, place the useful sound event at the intended timeline position, balance it against existing dialogue/music, and check the rendered result.

These are host-project tasks, not built-in Agent Audio engine/editor adapters. Preserve unrelated behavior and assets. Match the useful transient or audible event, not just the beginning or nominal duration of the generated file. Verify loop boundaries when looping is required; do not infer a clean loop from a prompt.

Check file existence, actual duration, sample rate and channels. With available tools, check silence, non-finite samples, peaks/clipping and the final mix. Such checks do not prove prompt adherence or artistic quality. Use actual listening or audio-analysis capabilities when available; never claim to have listened when only metadata was inspected. Without that capability, state the quality limit in the final report rather than inventing a listening assessment or forcing an intermediate user selection.

If generation or integration is blocked, do not silently substitute a paid service or procedural beep and present it as model-generated audio. Preserve completed work and report the specific missing part. Do not claim the whole sound workflow passed when only a WAV or a code reference was produced.

Final report

Report the finished result, where the audio was integrated, important asset paths, checks actually performed and remaining blockers or unverified quality. Do not expose hardware details unless relevant to performance or troubleshooting. Never claim CUDA, XPU or Apple acceleration unless the reported backend supports that claim. Model-license acceptance always remains a user action.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Audio Production AI skill do?

Generate and integrate local sound effects and other audio. Use when asked to build, finish or improve a game, edit a video, animate a scene, or create an interactive application or website where sound contributes to the requested result, even if audio is not mentioned. Also use for explicit audio requests. Do not use for unrelated analysis, documentation or refactoring, intentional silence, or when suitable audio already exists.

Why use Audio Production on TypingMind?

Because you install it once and use it with any model. Audio Production is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Audio Production in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AIEGOBOT/agent-audio/tree/main/skills/audio-production. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Audio Production?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Audio Production?

As many as you like. As long as a model supports skills, you can use Audio Production with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Audio Production AI skill free?

Yes. It is published on GitHub by AIEGOBOT under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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