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Game Audio Workflow

Community
witnesstodark
game-audio-workflow

Build and review game sound banks, map chosen takes to real events, and prepare or verify runtime playback with timing, repetition and mix limits. Use for unit voices, foley, impacts, UI cues and ambience.

Overview

Publisherwitnesstodark
Repositorymr-mak-workspace
Skill namegame-audio-workflow
Stars
545
Forks
183
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Game Audio Workflow 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/witnesstodark/mr-mak-workspace/tree/main/.agents/skills/game-audio-workflow
  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/witnesstodark/mr-mak-workspace.git /tmp/mr-mak-workspace
mkdir -p .claude/skills
cp -r /tmp/mr-mak-workspace/.agents/skills/game-audio-workflow .claude/skills/game-audio-workflow
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Game Audio Workflow 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 Game Audio Workflow 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 Game Audio Workflow 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.

Game audio workflow

Start with an event inventory and native motion/gameplay references. Separate unit voice, movement/gear, weapon air, material impact, victim reaction, UI, strategic alerts, music and ambience. A good recording can still be wrong for the event, camera distance or crowd mix.

Prepare and select material

For each event, record its meaning, motion anchor, source or generation route, desired length and review state. Reuse the user's chosen provider, voice and references. Inspect current tool capabilities instead of copying a stale model identifier. Keep generation IDs to recover pending jobs without duplicating them.

Use stable take IDs and direct local playback. Keep source, audition edit and runtime file distinct. Record cut points, fades, gain/pitch/time changes and source hashes. A compressed preview is not a lossless production master. Review actual samples for clipping, silence, format, duration and loop seams; technical checks do not establish the desired performance or tone.

Keep candidate, liked-for-comparison, accepted, integrated and mix-reviewed states separate. Preserve rejected history without presenting it as selected. Do not normalize or replace an accepted original silently. One accepted source may map to multiple events without duplicate files.

Follow the real event

Split an attack into optional effort, swing air, confirmed material contact and recipient reaction. A cancelled attack produces no contact sound. A death voice is separate from the body's actual landing. Footsteps follow planted-foot events or the project's verified distance/phase system; an arbitrary timer or a full audition loop may drift from the animation.

Play one appropriate speaker for a group command, with per-speaker repetition limits. Repeated path updates may affect movement without repeating the voice. Choose concurrency, variation and distance limits from the actual mix. Coalesce related alerts and fire a match result once from the authoritative result event, not whenever the HUD refreshes. Do not add a parry cue without a real parry event.

Integrate and listen

Use the project's mixer groups and persistent settings. Verify pause, mute, scene changes, interruption, visibility and source cleanup. Audition at gameplay distance and with a representative crowd, then check normal device output. Preserve the user's mix; do not replay unrelated narration during a focused test.

Deliver an event-to-file manifest, provenance/licences, original and derived files, selected states, event anchors, native listening capture and open mix decisions. Name which checks were technical and which were listened to.

Example: a robot's walk, swing, metal impact and shutdown. Successful delivery keeps the impact conditional on a hit, aligns steps, limits crowd repetition and preserves the approved takes. Dependencies: an audio editor or FFmpeg for edits, chosen generation/stock tools when requested, and engine access for integration.

Frequently asked questions

What does the Game Audio Workflow AI skill do?

Build and review game sound banks, map chosen takes to real events, and prepare or verify runtime playback with timing, repetition and mix limits. Use for unit voices, foley, impacts, UI cues and ambience.

Why use Game Audio Workflow on TypingMind?

Because you install it once and use it with any model. Game Audio Workflow 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 Game Audio Workflow in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/witnesstodark/mr-mak-workspace/tree/main/.agents/skills/game-audio-workflow. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Game Audio Workflow?

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 Game Audio Workflow?

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

Is the Game Audio Workflow AI skill free?

Yes. It is published on GitHub by witnesstodark 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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