Build real-time voice AI applications using Azure AI Voice Live SDK (azure-ai-voicelive). Use this skill when creating Python applications that need real-time bidirectional audio communication with...
Install with Tessl CLI
npx tessl i github:sickn33/antigravity-awesome-skills --skill azure-ai-voicelive-py86
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillEvaluation — 95%
↑ 1.46xAgent success when using this skill
Validation for skill structure
Function calling and session configuration
Correct import module
100%
100%
Async context manager
100%
100%
gpt-4o-realtime-preview model
0%
100%
DefaultAzureCredential used
100%
100%
credential_scopes parameter
0%
100%
FunctionTool import and usage
100%
100%
Session update with tools
100%
100%
Text and audio modalities
100%
100%
Event loop pattern
100%
100%
Function call output item
100%
100%
response.create after function output
100%
100%
asyncio entry point
100%
100%
Without context: $0.9230 · 6m 21s · 41 turns · 450 in / 7,299 out tokens
With context: $0.3213 · 2m 33s · 19 turns · 23 in / 3,648 out tokens
Manual turn control and audio streaming
Correct import path
0%
100%
Async context manager
60%
100%
base64 encoding for audio
100%
100%
input_audio_buffer.append usage
40%
100%
turn_detection disabled
100%
100%
Manual commit
66%
100%
Explicit response trigger
60%
100%
Conversation item injection
12%
0%
Transcript event handling
70%
50%
PCM16 audio format specification
100%
100%
Event loop pattern
100%
100%
asyncio entry point
100%
100%
Without context: $0.6353 · 7m 8s · 34 turns · 73 in / 8,633 out tokens
With context: $0.4104 · 3m 32s · 23 turns · 27 in / 4,065 out tokens
Interrupt handling, error handling, and semantic VAD
Correct import path
0%
100%
ConnectionClosed import
0%
100%
ConnectionError import
0%
100%
Separate exception handlers
100%
100%
Try/except around connect block
62%
100%
Azure Semantic VAD type
0%
100%
Telephony audio format
100%
100%
Barge-in: response.cancel()
50%
100%
Barge-in: output buffer clear
50%
100%
Event loop pattern
40%
100%
asyncio entry point
100%
100%
DefaultAzureCredential or AzureKeyCredential
100%
100%
Without context: $0.8317 · 8m 2s · 35 turns · 38 in / 14,069 out tokens
With context: $0.4281 · 3m 14s · 22 turns · 27 in / 4,629 out tokens
Table of Contents
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.