azure-ai-transcription-py

azure-ai-transcription-py is a skill for Claude Code from Ghosteken/agent-harness. It costs 31 tokens per session (448 once invoked), scanned A, original, MIT.

A Python SDK that turns speech recordings or live audio into written text, with timestamps and optional speaker identification. Speaker identification separates who said each part.

In plain words
What is it for?
Use it for live captions, meeting transcripts, and batch processing of audio files.
Why use it?
It removes the need to type recordings manually and helps distinguish speakers in conversations.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the agent-harness plugin — 173 skills, 13 commands, 12 agents shipped together

Good fit Use it for live captions, meeting transcripts, and batch processing of audio files.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ghosteken/agent-harness/azure-ai-transcription-py
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Ghosteken/agent-harness --skill azure-ai-transcription-py
Clone the repo
git clone --depth 1 https://github.com/Ghosteken/agent-harness

Made for: Claude Code.

Or install agent-harness, the plugin that ships this one along with the rest of its 173 skills, 13 commands, 12 agents.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for azure-ai-transcription-py

README.md
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Your own site
<a href="https://agentmods.dev/skills/ghosteken/agent-harness/azure-ai-transcription-py"><img src="https://agentmods.dev/badge/skills/ghosteken/agent-harness/azure-ai-transcription-py/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for azure-ai-transcription-py

Your own site · 80×15
<a href="https://agentmods.dev/skills/ghosteken/agent-harness/azure-ai-transcription-py"><img src="https://agentmods.dev/badge/skills/ghosteken/agent-harness/azure-ai-transcription-py.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 448 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00031 $0.00448
Opus 5 $0.00015 $0.00224
Sonnet 5 $0.00006 $0.00090
Haiku 4.5 $0.00003 $0.00045

Measured 8d ago against content hash e2e957cc11a1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

azure-ai-transcription-py scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

archive/skills-community/azure-ai-transcription-py/SKILL.md · 78 lines

What it actually says

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>

Authentication

Use subscription key authentication (DefaultAzureCredential is not supported for this client):

import os
from azure.ai.transcription import TranscriptionClient

client = TranscriptionClient(
    endpoint=os.environ["TRANSCRIPTION_ENDPOINT"],
    credential=os.environ["TRANSCRIPTION_KEY"]
)

Transcription (Batch)

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)

stream = client.begin_stream_transcription(locale="en-US")
stream.send_audio_file("audio.wav")
for event in stream:
    print(event.text)

Best Practices

  1. Enable diarization when multiple speakers are present
  2. Use batch transcription for long files stored in blob storage
  3. Capture timestamps for subtitle generation
  4. Specify language to improve recognition accuracy
  5. Handle streaming backpressure for real-time transcription
  6. Close transcription sessions when complete

When to Use

This skill is applicable to execute the workflow or actions described in the overview.

Limitations

  • Use this skill only when the task clearly matches the scope described above.
  • Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
  • Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 78 lines · 31 tokens per session scan A e2e957cc11a1

Subscribe to this mod's changes

azure-ai-transcription-py is a skill published in the GitHub repository Ghosteken/agent-harness (2 stars, last pushed yesterday), licensed MIT. It adds 31 tokens to every session and 448 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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