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Deepgram Agent Skill

Deepgram speech AI: transcribe audio to text and synthesize speech (TTS). Trigger phrases: deepgram, transcribe audio, speech to text, STT, deepgram tts.

857 tokens
context cost
SKILL.md, read when the skill is used
2
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
1 052
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/Anil-matcha/awesome-muse-connectors --skill deepgram

What comes with it

7 141 bytes besides the instruction
bin/deepgram.py

The instruction itself

7 sections, as written by the author

Deepgram

Purpose

Transcribe prerecorded audio files to text (with optional diarization, summaries, topics, sentiment) and synthesize speech with Deepgram's Aura voices. Reach for this when the user has an audio file to transcribe or wants spoken audio generated from text.

Tooling

All commands go through bin/deepgram.py. Auth uses exactly Authorization: Token <api_key> (not Bearer); the CLI wires it through the credential surrogate.

bin/deepgram.py auth
# {"ok": true, "projects": 2} on success

bin/deepgram.py projects
# list Deepgram projects (id, name)

bin/deepgram.py transcribe --file meeting.wav
# upload a local audio file, print the transcript JSON

bin/deepgram.py transcribe --file call.mp3 --model nova-3 --diarize --summarize --topics --sentiment
# transcript with speaker labels plus summary, topics and sentiment

bin/deepgram.py tts --text "Thanks for listening." --out thanks.mp3
# synthesize with an Aura voice to a local MP3 file; prints the saved path

Notes:

  • transcribe reads a local audio file, posts the bytes to POST /v1/listen, and prints the full transcript JSON. Content type is guessed from the file extension (wav, mp3, m4a, flac, ogg supported).
  • tts posts {"text": "..."} to POST /v1/speak?model=<model>&encoding=mp3 (default model aura-2-thalia-en, 2,000-char limit) and saves the audio to --out (default deepgram-output.mp3).
  • Live WebSocket STT (/v1/listen streaming) is real-time and outside CLI scope.

Auth

  • Provider id: deepgram (credential is collected as custom.deepgram)
  • Collection: Deepgram API key via the secure credential flow (credentials.request_api_access); create one in the Deepgram console
  • Allowed hosts: api.deepgram.com
  • Connect placement: custom_header:Authorization (the stored credential value must be exactly Token <api_key>, with the Token prefix; Bearer is not accepted)
  • Status check: bin/deepgram.py auth

Operating Rules

  • Usage is metered by audio duration (transcription) and characters (TTS). Transcribe and synthesize only what the user asked for; confirm before processing large batches.
  • API key and project management are confirmation-gated: confirm with the user before creating, rotating, or deleting keys or projects. This draft CLI is read/compute only; it does not manage keys or projects.
  • The transcript JSON can contain full conversation text. Treat transcripts as the user's private content; do not republish or forward them without instruction.
  • Never log or print the raw key; the CLI only ever handles the surrogate.

Files

  • SKILL.md
  • bin/deepgram.py

Maturity

🧪 Draft: written from Deepgram's public API docs with paths cross-checked at build time; not yet live-tested end-to-end. Key/project management and usage endpoints are not yet in the CLI.

How to use it

Copy the folder

Take anil-matcha/deepgram from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.