Agent skill

Azure Speech To Text

Transcribe audio to text using Azure AI Speech (Fast Transcription REST API).

Install Azure Speech To Text

skills CLI

$ npx skills add calesthio/OpenMontage --skill azure-speech-to-text -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install calesthio/OpenMontage azure-speech-to-text --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/calesthio/OpenMontage.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/azure-speech-to-text .claude/skills/azure-speech-to-text && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "azure-speech-to-text" agent skill from https://github.com/calesthio/OpenMontage/tree/main/.agents/skills/azure-speech-to-text into .claude/skills/azure-speech-to-text/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-speech-to-text", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/calesthio/OpenMontage/tree/main/.agents/skills/azure-speech-to-text

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add calesthio/OpenMontage --skill azure-speech-to-text -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install calesthio/OpenMontage azure-speech-to-text --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/calesthio/OpenMontage.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/azure-speech-to-text .agents/skills/azure-speech-to-text && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "azure-speech-to-text" agent skill from https://github.com/calesthio/OpenMontage/tree/main/.agents/skills/azure-speech-to-text into .agents/skills/azure-speech-to-text/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-speech-to-text", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add calesthio/OpenMontage --skill azure-speech-to-text -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install calesthio/OpenMontage azure-speech-to-text --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/calesthio/OpenMontage.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/azure-speech-to-text .cursor/skills/azure-speech-to-text && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "azure-speech-to-text" agent skill from https://github.com/calesthio/OpenMontage/tree/main/.agents/skills/azure-speech-to-text into .cursor/skills/azure-speech-to-text/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-speech-to-text", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/calesthio/OpenMontage.git --path .agents/skills/azure-speech-to-text

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add calesthio/OpenMontage --skill azure-speech-to-text -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install calesthio/OpenMontage azure-speech-to-text --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/calesthio/OpenMontage.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/azure-speech-to-text .gemini/skills/azure-speech-to-text && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "azure-speech-to-text" agent skill from https://github.com/calesthio/OpenMontage/tree/main/.agents/skills/azure-speech-to-text into .gemini/skills/azure-speech-to-text/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-speech-to-text", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install calesthio/OpenMontage azure-speech-to-text

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add calesthio/OpenMontage --skill azure-speech-to-text -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/calesthio/OpenMontage.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/azure-speech-to-text .github/skills/azure-speech-to-text && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "azure-speech-to-text" agent skill from https://github.com/calesthio/OpenMontage/tree/main/.agents/skills/azure-speech-to-text into .github/skills/azure-speech-to-text/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-speech-to-text", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add calesthio/OpenMontage --skill azure-speech-to-text -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install calesthio/OpenMontage azure-speech-to-text --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/calesthio/OpenMontage.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/azure-speech-to-text .opencode/skills/azure-speech-to-text && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "azure-speech-to-text" agent skill from https://github.com/calesthio/OpenMontage/tree/main/.agents/skills/azure-speech-to-text into .opencode/skills/azure-speech-to-text/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-speech-to-text", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: azure-speech-to-text
GitHub stars: 66k
Token cost: ~1.3k tokens
SKILL.md length: 423 words
Files: 1
Skills in repo: 41
Repo updated: Oct 3, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Transcribe audio to text using Azure AI Speech (Fast Transcription REST API).

Converting audio/video to text
SKILL.md covers Why Fast Transcription (not…, Setup, Using it in a pipeline and Parameters that matter, plus 2 more sections
Needs AZURE_SPEECH_KEY
Generating subtitles

What it does

Azure Speech To Text is an agent skill from calesthio/OpenMontage. Transcribe audio to text using Azure AI Speech (Fast Transcription REST API). Use when converting audio/video to text, generating subtitles, or processing spoken content in OpenMontage. Optional cloud STT provider — preferred when AZURESPEECHKEY is configured; the local faster-whisper transcriber is the default offline path.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: Requires internet access and an Azure AI Speech resource (AZURESPEECHKEY + AZURESPEECHREGION).

It sits in Media & Creative, covering Transcription. It works with Azure AI Speech, Whisper and Microsoft Azure. The repository describes itself as: World's first open-source, agentic video production system. 12 production pipelines, 100+ tools, 700+ agent skill and production-knowledge files. Turn your AI coding assistant… The licence is MIT.

When your agent uses it

Converting audio/video to text
Generating subtitles
Processing spoken content in OpenMontage

Example prompts

“/azure-speech-to-text”

Requirements

Python 3
A credential in AZURE_SPEECH_KEY
Compatibility (from SKILL.md): Requires internet access and an Azure AI Speech resource (AZURE_SPEECH_KEY + AZURE_SPEECH_REGION).

What it can do on your machine

Read from SKILL.md and the folder at commit 9327439. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are bash, python and json).
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
- learn.microsoft.com
- portal.azure.com
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
- AZURE_SPEECH_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Compatibility
Requires internet access and an Azure AI Speech resource (AZURE_SPEECH_KEY + AZURE_SPEECH_REGION).
From compatibility in the SKILL.md frontmatter.

Context cost

Azure Speech To Text loads about 1.3k tokens when it runs. Until then it costs about 88 tokens; SKILL.md has 423 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~88
When it runs · the whole SKILL.md, loaded when a task matches: ~1.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from calesthio/OpenMontage at commit 9327439, republished under its MIT licence (© calesthio). 423 words, ~1,316 tokens.

Download SKILL.mdSave it as .claude/skills/azure-speech-to-text/SKILL.md (or your agent's skills folder).

name: azure-speech-to-text
description: Transcribe audio to text using Azure AI Speech (Fast Transcription REST API). Use when converting audio/video to text, generating subtitles, or processing spoken content in OpenMontage. Optional cloud STT provider — preferred when AZURE_SPEECH_KEY is configured; the local faster-whisper `transcriber` is the default offline path.
compatibility: Requires internet access and an Azure AI Speech resource (AZURE_SPEECH_KEY + AZURE_SPEECH_REGION).
license: MIT

Azure AI Speech — Speech-to-Text

Transcribe audio to text with Azure Fast Transcription — synchronous, word-level timestamps, speaker diarization, and multi-language identification. In OpenMontage this is exposed through the azure_stt tool (capability=analysis, provider=azure). It is an optional cloud STT provider — when AZURE_SPEECH_KEY is configured, prefer it for cloud transcription. The local transcriber tool (faster-whisper) remains the default offline path and the fallback when Azure is unavailable.

Docs: Fast Transcription · Speech service overview

Why Fast Transcription (not Batch)

Azure exposes three STT surfaces. OpenMontage uses Fast Transcription because the pipeline transcribes local audio files:

Surface	Input	Latency	Needs
Fast Transcription (used here)	local file, multipart POST	synchronous, sub-real-time	key + region
Batch Transcription	audio at a URL (Blob + SAS)	async job + polling	Blob storage plumbing
Speech SDK (`spx`)	mic / stream / file	streaming	native `azure-cognitiveservices-speech` package

Fast Transcription needs no Blob storage, no SAS URLs, and no native SDK — just requests and the two env vars.

Setup

Create a Speech resource in the Azure portal; copy the key and region from its Keys and Endpoint page.

bash

export AZURE_SPEECH_KEY=your_speech_resource_key
export AZURE_SPEECH_REGION=eastus          # your resource's region
# export AZURE_SPEECH_ENDPOINT=https://...  # optional: overrides region

azure_stt reports AVAILABLE once AZURE_SPEECH_KEY plus either AZURE_SPEECH_REGION or AZURE_SPEECH_ENDPOINT are set.

Using it in a pipeline

Prefer azure_stt over transcriber unless the run must be offline. Its output matches the transcriber schema exactly, so it is a drop-in for subtitle_gen and any stage that consumes a transcript.

python

from tools.tool_registry import registry
registry.discover()
stt = registry._tools["azure_stt"]

result = stt.execute({
    "input_path": "projects/my-video/assets/audio/narration.mp3",
    # "language": "en",          # ISO 639-1 or BCP-47 ("en-US"); omit for auto-ID
    # "diarize": True,           # speaker labels, no HuggingFace token needed
    # "max_speakers": 4,
    "output_dir": "projects/my-video/artifacts",
})
if result.success:
    segs = result.data["segments"]          # [{id,start,end,text,words:[...]}]
    words = result.data["word_timestamps"]  # flat [{word,start,end,probability}]

If azure_stt is unavailable (no key) or errors, fall back to transcriber (local whisper) — its execute signature and output are identical.

Show full SKILL.md (183 more words)Show less

Parameters that matter

language — pass an ISO code ("en") or a full locale ("en-US"). Pin it when you know the language; it is faster and more accurate than auto-ID.
candidate_locales — when language is omitted, Azure runs language identification across this shortlist. Narrow it to the languages you actually expect; a huge list slows detection and invites misclassification.
diarize / max_speakers — enable for multi-speaker audio (interviews, podcasts). Set max_speakers to the real upper bound.
profanity_filter — None | Masked (default) | Removed | Tags.

Response shape (mapped to the transcriber schema)

The raw Azure response (phrases[] with offsetMilliseconds / words[]) is converted to seconds and the OpenMontage transcript schema:

json

{
  "segments": [
    {"id": 0, "start": 0.0, "end": 2.4, "text": "Hello world",
     "speaker": 1,
     "words": [{"word": "Hello", "start": 0.0, "end": 0.5, "probability": 0.98}]}
  ],
  "word_timestamps": [{"word": "Hello", "start": 0.0, "end": 0.5, "probability": 0.98}],
  "language": "en-US",
  "duration_seconds": 2.4,
  "provider": "azure"
}

Note: Fast Transcription has no per-word confidence, so each word carries the phrase confidence in probability.

Limits & tips

Single file up to ~2 hours / a few hundred MB per request. For longer or bulk jobs, use Azure Batch Transcription instead.
Send clean audio (16 kHz+ mono is plenty). Transcode video to audio first if you only need speech — smaller upload, same result.
Verify timing: word timestamps drive subtitle cues in subtitle_gen. Spot-check the first and last cues against the source audio.

Files

Just SKILL.md in .agents/skills/azure-speech-to-text of calesthio/OpenMontage.

Open the folder on GitHubat commit 9327439

Compare with similar skills

Azure Speech To Text next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Azure Speech To Text compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Azure Speech To Text this skillcalesthio/OpenMontage	66k	—	~1.3k	Automated safety check: Pass	MIT	8 days ago
Azure Speech To Text REST Pymicrosoft/skills	3.1k	5 repos	~3k	Automated safety check: Pass	MIT	2 days ago
Deepgram Migration Deep Divejeremylongshore/tons-of-skills-marketplace	2.8k	—	~3.3k	Automated safety check: Pass	MIT	yesterday
Azure AI Voicelive Pymicrosoft/skills	3.1k	—	~2.9k	Automated safety check: Pass	MIT	2 days ago
9Router Speech-to-Textdecolua/9router	31k	—	~914	Automated safety check: Pass	MIT	3 days ago
ShortsAgriciDaniel/claude-shorts	219	—	~3.2k	Automated safety check: Notes	MIT	3 mo ago

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Questions about Azure Speech To Text

What does Azure Speech To Text do?

Transcribe audio to text using Azure AI Speech (Fast Transcription REST API). Azure Speech To Text is an agent skill from calesthio/OpenMontage. Transcribe audio to text using Azure AI Speech (Fast Transcription REST API).

When should I use Azure Speech To Text?

Azure Speech To Text fits situations like: converting audio/video to text; generating subtitles; processing spoken content in OpenMontage.

How do I install Azure Speech To Text in Claude Code?

Run `npx skills add calesthio/OpenMontage --skill azure-speech-to-text -a claude-code`. Or copy the skill folder (.agents/skills/azure-speech-to-text in calesthio/OpenMontage) into .claude/skills/azure-speech-to-text in your project. Claude Code loads it when a task matches its description.

How do I install Azure Speech To Text in Codex?

Run `npx skills add calesthio/OpenMontage --skill azure-speech-to-text -a codex`. Or copy the skill folder (.agents/skills/azure-speech-to-text in calesthio/OpenMontage) into .agents/skills/azure-speech-to-text in your project. Codex loads it when a task matches its description.

Can I use Azure Speech To Text in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add calesthio/OpenMontage --skill azure-speech-to-text -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/azure-speech-to-text, .gemini/skills/azure-speech-to-text, .github/skills/azure-speech-to-text and .opencode/skills/azure-speech-to-text in your project.

What does Azure Speech To Text need to run?

Going by SKILL.md and its folder, Azure Speech To Text needs credentials named AZURE_SPEECH_KEY. Our summary lists: Python 3; A credential in AZURE_SPEECH_KEY. Compatibility (from SKILL.md): Requires internet access and an Azure AI Speech resource (AZURE_SPEECH_KEY + AZURE_SPEECH_REGION)..

Does Azure Speech To Text access the network?

SKILL.md names 2 domains. As links in the text: learn.microsoft.com and portal.azure.com. This is read from the text; nothing was executed.

Is Azure Speech To Text safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Azure Speech To Text use?

Azure Speech To Text is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Azure Speech To Text use?

About 1.3k tokens (SKILL.md is roughly 5.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Azure Speech To Text?

Skills that share tags, products or a category with Azure Speech To Text: Azure Speech To Text REST Py (microsoft/skills, 3.1k stars), Deepgram Migration Deep Dive (jeremylongshore/tons-of-skills-marketplace, 2.8k stars), Azure AI Voicelive Py (microsoft/skills, 3.1k stars) and 9Router Speech-to-Text (decolua/9router, 31k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Azure Speech To Text?

calesthio (a GitHub user) maintains it in calesthio/OpenMontage, which has 65,930 GitHub stars. The repository holds 41 skills in this directory. The repository was last updated on October 3, 2026.

Source: calesthio/OpenMontage on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Azure Speech To Text

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Compatibility

Context cost

Safety

SKILL.md

Azure AI Speech — Speech-to-Text

Why Fast Transcription (not Batch)

Setup

Using it in a pipeline

Parameters that matter

Response shape (mapped to the transcriber schema)

Limits & tips

Files

Compare with similar skills

Similar skills

More from calesthio/OpenMontage

Related

Questions about Azure Speech To Text