Azure AI Transcription Py Agent Skill

| Azure AI Transcription SDK for Python. Use for real-time and batch speech-to-text transcription with timestamps and diarization.

2k tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

64 d ago

last touched

this folder, not the whole repository

Install

one command, takes just this skill from the repository

npx skills add https://github.com/microsoft/skills --skill azure-ai-transcription-py

What comes with it

4 863 bytes besides the instruction

references/capabilities.md

references/non-hero-scenarios.md

The instruction itself

8 sections, as written by the author

Azure AI Transcription SDK for Python

Client library for Azure AI Transcription (speech-to-text) with real-time and batch transcription.

Installation

pip install azure-ai-transcription

Environment Variables

TRANSCRIPTION_ENDPOINT=https://<resource>.cognitiveservices.azure.com
TRANSCRIPTION_KEY=<your-key>  # For key auth; not needed when using DefaultAzureCredential/TokenCredential

Authentication & Lifecycle

> 🔑 Two rules apply to every code sample below:

> 1. Two auth modes are supported: AzureKeyCredential(os.environ["TRANSCRIPTION_KEY"]) for key-based auth, or DefaultAzureCredential() / any TokenCredential for Entra ID. Prefer DefaultAzureCredential in production; never hardcode credentials in code.

> 2. Wrap every client in a context manager so HTTP transports and sockets are released deterministically:

> - Sync: with <Client>(...) as client:

> - Async: async with <Client>(...) as client:

> Snippets may abbreviate this setup, but production code should always follow both rules.

Use subscription key authentication:

import os
from azure.core.credentials import AzureKeyCredential
from azure.ai.transcription import TranscriptionClient

with TranscriptionClient(
    endpoint=os.environ["TRANSCRIPTION_ENDPOINT"],
    credential=AzureKeyCredential(os.environ["TRANSCRIPTION_KEY"]),
) as client:
    transcriptions = list(client.list_transcriptions())

Transcription (Batch)

import os
from azure.core.credentials import AzureKeyCredential
from azure.ai.transcription import TranscriptionClient

with TranscriptionClient(
    endpoint=os.environ["TRANSCRIPTION_ENDPOINT"],
    credential=AzureKeyCredential(os.environ["TRANSCRIPTION_KEY"]),
) as client:
    job = client.begin_transcription(
        name="meeting-transcription",
        locale="en-US",
        content_urls=["https://<storage>/audio.wav"],
        diarization_enabled=True,
    )
    result = job.result()
    print(result.status)

Transcription (Real-time)

import os
from azure.core.credentials import AzureKeyCredential
from azure.ai.transcription import TranscriptionClient

with TranscriptionClient(
    endpoint=os.environ["TRANSCRIPTION_ENDPOINT"],
    credential=AzureKeyCredential(os.environ["TRANSCRIPTION_KEY"]),
) as client:
    stream = client.begin_stream_transcription(locale="en-US")
    stream.send_audio_file("audio.wav")
    for event in stream:
        print(event.text)

Best Practices

Pick sync OR async and stay consistent. Do not mix azure.xxx sync clients with azure.xxx.aio async clients in the same call path. Choose one mode per module.
Always use context managers for clients and async credentials. Wrap every client in with Client(...) as client: (sync) or async with Client(...) as client: (async). For async DefaultAzureCredential from azure.identity.aio, also use async with credential: so tokens and transports are cleaned up.
Enable diarization when multiple speakers are present
Use batch transcription for long files stored in blob storage
Capture timestamps for subtitle generation
Specify language to improve recognition accuracy
Handle streaming backpressure for real-time transcription
Close transcription sessions when complete

Reference Files

| File | Contents |

|------|----------|

| references/capabilities.md | Additional non-hero capabilities, operation-group coverage, and production checklists. |

| references/non-hero-scenarios.md | Dedicated non-hero examples for secondary/advanced scenarios. |

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How to use it

Copy the folder

Take microsoft/azure-ai-transcription-py from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

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Install what it needs

The instructions reference pip. Without those the skill loads but fails at the first command.