agentleFS
weininghuiweininghui/skills/voice-agent/SKILL.md

voice-agent

Skill1 starsChanged 14 days agoMITView on GitHub

Local Voice Input/Output for Agents using the AI Voice Agent API.

3 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

6 rules. About 0 are common, 3 are distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Audio First: When the user communicates via audio (files), your PRIMARY mode of response is Audio File.

    line 20
  2. Distinctive:

    Silent Delivery: When sending an audio response, DO NOT send a text explanation like "I sent an audio".

    line 21
  3. Very specific:

    Use transcribe to read it.

    line 24
  4. Very specific:

    Use synthesize to generate the audio file.

    line 26
  5. Distinctive:

    STOP: Do not add text commentary.

    line 28
  6. Very specific:

    Failure Handling: If health fails or connection errors occur, do not attempt service management from this skill.

    line 29

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Voice Agent

This skill allows you to speak and listen to the user using a local Voice Agent API. It is client-only and does not start containers or services. It uses local Whisper for Speech-to-Text transcription and AWS Polly for Text-to-Speech generation.

Prerequisite

Requires a running backend API at http://localhost:8000. Backend setup instructions are in this repository:

  • README.md
  • walkthrough.md
  • DOCKER_README.md

Behavior Guidelines

  • Audio First: When the user communicates via audio (files), your PRIMARY mode of response is Audio File.
  • Silent Delivery: When sending an audio response, DO NOT send a text explanation like "I sent an audio". Just send the audio file.
  • Workflow:
    1. User sends audio.
    2. Use transcribe to read it.
    3. You think of a response.
    4. Use synthesize to generate the audio file.
    5. You send the file.
    6. STOP. Do not add text commentary.
  • Failure Handling: If health fails or connection errors occur, do not attempt service management from this skill. Ask the user to start or fix the backend using the repository docs.

Tools

Transcribe File

To transcribe an audio file with local Whisper STT, run the client script with the transcribe command.

python3 {baseDir}/scripts/client.py transcribe "/path/to/audio/file.ogg"

Synthesize to File

To generate audio from text with AWS Polly TTS and save it to a file, run the client script with the synthesize command.

python3 {baseDir}/scripts/client.py synthesize "Text to speak" --output "/path/to/output.mp3"

Health Check

To check if the voice agent API is running and healthy:

python3 {baseDir}/scripts/client.py health

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.