Watch
mathiaschu/watch
Watch a video from YouTube, Instagram, X/Twitter, Vimeo, TikTok or any of ~1800 yt-dlp sites (or a local path).
Azure Speech to Text REST API for short audio (Python). An agent skill from microsoft/skills.
$ npx skills add microsoft/skills --skill azure-speech-to-text-rest-py -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install microsoft/skills azure-speech-to-text-rest-py --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-py .claude/skills/azure-speech-to-text-rest-py && rm -rf skills-srcUse ~/.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/
Install the "azure-speech-to-text-rest-py" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-py into .claude/skills/azure-speech-to-text-rest-py/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-speech-to-text-rest-py", 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 install https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-pyType 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.
$ npx skills add microsoft/skills --skill azure-speech-to-text-rest-py -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install microsoft/skills azure-speech-to-text-rest-py --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-py .agents/skills/azure-speech-to-text-rest-py && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "azure-speech-to-text-rest-py" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-py into .agents/skills/azure-speech-to-text-rest-py/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-speech-to-text-rest-py", 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.
$ npx skills add microsoft/skills --skill azure-speech-to-text-rest-py -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install microsoft/skills azure-speech-to-text-rest-py --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-py .cursor/skills/azure-speech-to-text-rest-py && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "azure-speech-to-text-rest-py" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-py into .cursor/skills/azure-speech-to-text-rest-py/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-speech-to-text-rest-py", 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 https://github.com/microsoft/skills.git --path .github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-py--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add microsoft/skills --skill azure-speech-to-text-rest-py -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install microsoft/skills azure-speech-to-text-rest-py --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-py .gemini/skills/azure-speech-to-text-rest-py && rm -rf skills-srcUse ~/.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/
Install the "azure-speech-to-text-rest-py" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-py into .gemini/skills/azure-speech-to-text-rest-py/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-speech-to-text-rest-py", 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.
$ gh skill install microsoft/skills azure-speech-to-text-rest-pyInstalls 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).
$ npx skills add microsoft/skills --skill azure-speech-to-text-rest-py -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/.github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-py .github/skills/azure-speech-to-text-rest-py && rm -rf skills-srcUse ~/.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/
Install the "azure-speech-to-text-rest-py" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-py into .github/skills/azure-speech-to-text-rest-py/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-speech-to-text-rest-py", 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.
$ npx skills add microsoft/skills --skill azure-speech-to-text-rest-py -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install microsoft/skills azure-speech-to-text-rest-py --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-py .opencode/skills/azure-speech-to-text-rest-py && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "azure-speech-to-text-rest-py" agent skill from https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-py into .opencode/skills/azure-speech-to-text-rest-py/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "azure-speech-to-text-rest-py", 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.
azure-speech-to-text-rest-pyAzure Speech to Text REST API for short audio (Python). An agent skill from microsoft/skills.
Azure Speech To Text REST Py is an agent skill from microsoft/skills, published by the product's own GitHub organization. Azure Speech to Text REST API for short audio (Python). Use for simple speech recognition of audio files up to 60 seconds without the Speech SDK. Triggers: "speech to text REST", "short audio transcription", "speech recognition REST API", "STT REST", "recognize speech REST". DO NOT USE FOR: Long audio (60 seconds), real-time streaming, batch transcription, custom speech models, speech translation. Use Speech SDK or Batch Transcription API instead.
Its SKILL.md is about 3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/pronunciation-assessment.md`).
It sits in Media & Creative, covering Transcription, Speech recognition and synthesis and REST APIs. It works with Azure AI Speech, Microsoft Azure and Python. The repository describes itself as: Skills, MCP servers, Custom Agents, Agents.md for SDKs to ground Coding Agents. The licence is MIT.
3 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit d5741a1. It shows what the files ask for, not the result of running them.
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.
Shell commands in SKILL.md call:
pipFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
azure.microsoft.comportal.azure.comlearn.microsoft.comFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
AZURE_SPEECH_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Azure Speech To Text REST Py loads about 3k tokens when it runs, and up to ~5k if it reads all its reference files. Until then it costs about 120 tokens; SKILL.md has 489 words of instructions outside code blocks.
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.
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.
The full file from microsoft/skills at commit d5741a1, republished under its MIT licence (© microsoft). 489 words, ~3,013 tokens.
.claude/skills/azure-speech-to-text-rest-py/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Simple REST API for speech-to-text transcription of short audio files (up to 60 seconds). No SDK required - just HTTP requests.
# Required
AZURE_SPEECH_KEY=<your-speech-resource-key>
AZURE_SPEECH_REGION=<region> # e.g., eastus, westus2, westeurope
# Alternative: Use endpoint directly
AZURE_SPEECH_ENDPOINT=https://<region>.stt.speech.microsoft.compip install requests🔑 Two rules apply to every code sample below:
- Two auth modes are supported. Use a subscription key (
Ocp-Apim-Subscription-Keyheader) for quick access, or a Microsoft Entra token (including one acquired withDefaultAzureCredential) via theAuthorizationrequest header (see "Option 2" below). Never hardcode credentials in source.- Use context managers for files and HTTP resources so file handles and network connections are released deterministically:
- Sync:
with open(...) as f:and (when reusing connections)with requests.Session() as session:- Async:
async with aiohttp.ClientSession() as session:Snippets may abbreviate this setup, but production code should always follow both rules.
import os
import requests
def transcribe_audio(audio_file_path: str, language: str = "en-US") -> dict:
"""Transcribe short audio file (max 60 seconds) using REST API."""
region = os.environ["AZURE_SPEECH_REGION"]
api_key = os.environ["AZURE_SPEECH_KEY"]
url = f"https://{region}.stt.speech.microsoft.com/speech/recognition/conversation/cognitiveservices/v1"
headers = {
"Ocp-Apim-Subscription-Key": api_key,
"Content-Type": "audio/wav; codecs=audio/pcm; samplerate=16000",
"Accept": "application/json"
}
params = {
"language": language,
"format": "detailed" # or "simple"
}
with open(audio_file_path, "rb") as audio_file:
response = requests.post(url, headers=headers, params=params, data=audio_file)
response.raise_for_status()
return response.json()
# Usage
result = transcribe_audio("audio.wav", "en-US")
print(result["DisplayText"])| Format | Codec | Sample Rate | Notes |
|---|---|---|---|
| WAV | PCM | 16 kHz, mono | Recommended |
| OGG | OPUS | 16 kHz, mono | Smaller file size |
Limitations:
# WAV PCM 16kHz
wav_headers = {
"Content-Type": "audio/wav; codecs=audio/pcm; samplerate=16000"
}
# OGG OPUS
ogg_headers = {
"Content-Type": "audio/ogg; codecs=opus"
}params = {"language": "en-US", "format": "simple"}{
"RecognitionStatus": "Success",
"DisplayText": "Remind me to buy 5 pencils.",
"Offset": "1236645672289",
"Duration": "1236645672289"
}params = {"language": "en-US", "format": "detailed"}{
"RecognitionStatus": "Success",
"Offset": "1236645672289",
"Duration": "1236645672289",
"NBest": [
{
"Confidence": 0.9052885,
"Display": "What's the weather like?",
"ITN": "what's the weather like",
"Lexical": "what's the weather like",
"MaskedITN": "what's the weather like"
}
]
}For lower latency, stream audio in chunks:
import os
import requests
def transcribe_chunked(audio_file_path: str, language: str = "en-US") -> dict:
"""Stream audio in chunks for lower latency."""
region = os.environ["AZURE_SPEECH_REGION"]
api_key = os.environ["AZURE_SPEECH_KEY"]
url = f"https://{region}.stt.speech.microsoft.com/speech/recognition/conversation/cognitiveservices/v1"
headers = {
"Ocp-Apim-Subscription-Key": api_key,
"Content-Type": "audio/wav; codecs=audio/pcm; samplerate=16000",
"Accept": "application/json",
"Transfer-Encoding": "chunked",
"Expect": "100-continue"
}
params = {"language": language, "format": "detailed"}
def generate_chunks(file_path: str, chunk_size: int = 1024):
with open(file_path, "rb") as f:
while chunk := f.read(chunk_size):
yield chunk
response = requests.post(
url,
headers=headers,
params=params,
data=generate_chunks(audio_file_path)
)
response.raise_for_status()
return response.json()headers = {
"Ocp-Apim-Subscription-Key": os.environ["AZURE_SPEECH_KEY"]
}import requests
import os
def get_access_token() -> str:
"""Get access token from the token endpoint."""
region = os.environ["AZURE_SPEECH_REGION"]
api_key = os.environ["AZURE_SPEECH_KEY"]
token_url = f"https://{region}.api.cognitive.microsoft.com/sts/v1.0/issueToken"
response = requests.post(
token_url,
headers={
"Ocp-Apim-Subscription-Key": api_key,
"Content-Type": "application/x-www-form-urlencoded",
"Content-Length": "0"
}
)
response.raise_for_status()
return response.text
# Use token in requests (valid for 10 minutes)
token = get_access_token()
headers = {
"Authorization": f"Bearer {token}",
"Content-Type": "audio/wav; codecs=audio/pcm; samplerate=16000",
"Accept": "application/json"
}| Parameter | Required | Values | Description |
|---|---|---|---|
language | Yes | en-US, de-DE, etc. | Language of speech |
format | No | simple, detailed | Result format (default: simple) |
profanity | No | masked, removed, raw | Profanity handling (default: masked) |
| Status | Description |
|---|---|
Success | Recognition succeeded |
NoMatch | Speech detected but no words matched |
InitialSilenceTimeout | Only silence detected |
BabbleTimeout | Only noise detected |
Error | Internal service error |
# Mask profanity with asterisks (default)
params = {"language": "en-US", "profanity": "masked"}
# Remove profanity entirely
params = {"language": "en-US", "profanity": "removed"}
# Include profanity as-is
params = {"language": "en-US", "profanity": "raw"}import requests
def transcribe_with_error_handling(audio_path: str, language: str = "en-US") -> dict | None:
"""Transcribe with proper error handling."""
region = os.environ["AZURE_SPEECH_REGION"]
api_key = os.environ["AZURE_SPEECH_KEY"]
url = f"https://{region}.stt.speech.microsoft.com/speech/recognition/conversation/cognitiveservices/v1"
try:
with open(audio_path, "rb") as audio_file:
response = requests.post(
url,
headers={
"Ocp-Apim-Subscription-Key": api_key,
"Content-Type": "audio/wav; codecs=audio/pcm; samplerate=16000",
"Accept": "application/json"
},
params={"language": language, "format": "detailed"},
data=audio_file
)
if response.status_code == 200:
result = response.json()
if result.get("RecognitionStatus") == "Success":
return result
else:
print(f"Recognition failed: {result.get('RecognitionStatus')}")
return None
elif response.status_code == 400:
print(f"Bad request: Check language code or audio format")
elif response.status_code == 401:
print(f"Unauthorized: Check API key or token")
elif response.status_code == 403:
print(f"Forbidden: Missing authorization header")
else:
print(f"Error {response.status_code}: {response.text}")
return None
except requests.exceptions.RequestException as e:
print(f"Request failed: {e}")
return Noneimport os
import aiohttp
import asyncio
async def transcribe_async(audio_file_path: str, language: str = "en-US") -> dict:
"""Async version using aiohttp."""
region = os.environ["AZURE_SPEECH_REGION"]
api_key = os.environ["AZURE_SPEECH_KEY"]
url = f"https://{region}.stt.speech.microsoft.com/speech/recognition/conversation/cognitiveservices/v1"
headers = {
"Ocp-Apim-Subscription-Key": api_key,
"Content-Type": "audio/wav; codecs=audio/pcm; samplerate=16000",
"Accept": "application/json"
}
params = {"language": language, "format": "detailed"}
async with aiohttp.ClientSession() as session:
with open(audio_file_path, "rb") as f:
audio_data = f.read()
async with session.post(url, headers=headers, params=params, data=audio_data) as response:
response.raise_for_status()
return await response.json()
# Usage
result = asyncio.run(transcribe_async("audio.wav", "en-US"))
print(result["DisplayText"])Common language codes (see full list):
| Code | Language |
|---|---|
en-US | English (US) |
en-GB | English (UK) |
de-DE | German |
fr-FR | French |
es-ES | Spanish (Spain) |
es-MX | Spanish (Mexico) |
zh-CN | Chinese (Mandarin) |
ja-JP | Japanese |
ko-KR | Korean |
pt-BR | Portuguese (Brazil) |
azure.xxx sync clients with azure.xxx.aio async clients in the same call path. Choose one mode per module.with open(...) as f: and (when reusing connections) with requests.Session() as session: for sync code, or async with aiohttp.ClientSession() as session: for async code.Use the Speech SDK or Batch Transcription API instead when you need:
| File | Contents |
|---|---|
| references/pronunciation-assessment.md | Pronunciation assessment parameters and scoring |
© microsoft, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (references) in .github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-py of microsoft/skills.
Open the folder on GitHubat commit d5741a1
We found 14 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 5 other GitHub owners. This page covers the copy in microsoft/skills, which our catalogue first saw on October 7, 2026.
Azure Speech To Text REST Py 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Azure Speech To Text REST Py this skillmicrosoft/skills | 3.1k | 5 repos | ~3k | Automated safety check: Pass | MIT | |
| Watchmathiaschu/watch | 142 | — | ~4k | Automated safety check: Warn | MIT | |
| Speech Engineelevenlabs/skills | 482 | — | ~2.5k | Automated safety check: Warn | MIT | |
| Azure AImicrosoft/GitHub-Copilot-for-Azure | 255 | 1 repos | ~852 | Automated safety check: Pass | MIT | |
| Douyin DownloaderOpenMinis/MinisSkills | 446 | — | ~1.4k | Automated safety check: Pass | MIT | |
| Watch Video Q&Abradautomates/claude-video | 18k | — | ~4.3k | Automated safety check: Notes | MIT |
mathiaschu/watch
Watch a video from YouTube, Instagram, X/Twitter, Vimeo, TikTok or any of ~1800 yt-dlp sites (or a local path).
elevenlabs/skills
Add real-time voice conversations to a custom agent runtime with ElevenLabs Speech Engine.
microsoft/GitHub-Copilot-for-Azure
A skill your agent uses for Azure AI: Search, Speech, OpenAI, Document Intelligence.
OpenMinis/MinisSkills
Download Douyin (TikTok) videos from share links. An agent skill from OpenMinis/MinisSkills.
bradautomates/claude-video
Lets the agent answer questions about a video from a URL or local file by downloading it, extracting frames and a transcript, or by sending it to Gemini's video model.
HUANGCHIHHUNGLeo/claude-real-video
Watch a video for the user. An agent skill from HUANGCHIHHUNGLeo/claude-real-video.
microsoft/skills
Covers producer, consumer, and checkpoint-store setup for Azure Event Hubs streaming in Python, with Entra ID auth and partition targeting.
microsoft/skills
Builds podcast-style audio narration from text with Azure OpenAI's GPT Realtime Mini over WebSocket, from a Python FastAPI backend to a React player.
microsoft/skills
Build dark-themed React applications using Tailwind CSS with custom theming, glassmorphism effects, and Framer Motion animations.
microsoft/skills
Create Pydantic models following the multi-model pattern with Base, Create, Update, Response, and InDB variants.
microsoft/skills
Reference for building on Microsoft Foundry with the azure-ai-projects Python SDK: project clients, versioned agents, evaluations, connections, datasets and indexes.
microsoft/skills
Guide for creating effective skills for AI coding agents working with Azure SDKs and Microsoft Foundry services.
Works with
Azure Speech to Text REST API for short audio (Python). An agent skill from microsoft/skills. Azure Speech To Text REST Py is an agent skill from microsoft/skills, published by the product's own GitHub organization. Azure Speech to Text REST API for short audio (Python).
Azure Speech To Text REST Py fits situations like: simple speech recognition of audio files up to 60 seconds without the Speech SDK; : Long audio (60 seconds); real-time streaming; batch transcription.
Run `npx skills add microsoft/skills --skill azure-speech-to-text-rest-py -a claude-code`. Or copy the skill folder (.github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-py in microsoft/skills) into .claude/skills/azure-speech-to-text-rest-py in your project. Claude Code loads it when a task matches its description.
Run `npx skills add microsoft/skills --skill azure-speech-to-text-rest-py -a codex`. Or copy the skill folder (.github/plugins/azure-sdk-python/skills/azure-speech-to-text-rest-py in microsoft/skills) into .agents/skills/azure-speech-to-text-rest-py in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add microsoft/skills --skill azure-speech-to-text-rest-py -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-rest-py, .gemini/skills/azure-speech-to-text-rest-py, .github/skills/azure-speech-to-text-rest-py and .opencode/skills/azure-speech-to-text-rest-py in your project.
Going by SKILL.md and its folder, Azure Speech To Text REST Py needs the command-line tools its instructions call (pip) and credentials named AZURE_SPEECH_KEY. Our summary lists: Python 3; A credential in AZURE_SPEECH_KEY.
SKILL.md names 3 domains. As links in the text: azure.microsoft.com, portal.azure.com and learn.microsoft.com. This is read from the text; nothing was executed.
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.
Azure Speech To Text REST Py is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 3k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.9k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Azure Speech To Text REST Py: Watch (mathiaschu/watch, 142 stars), Speech Engine (elevenlabs/skills, 482 stars), Azure AI (microsoft/GitHub-Copilot-for-Azure, 255 stars) and Douyin Downloader (OpenMinis/MinisSkills, 446 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
microsoft (a GitHub organization, an official publisher) maintains it in microsoft/skills, which has 3,097 GitHub stars. The repository holds 150 skills in this directory. The repository was last updated on October 9, 2026.
Source: microsoft/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.