基于 SOC 职业分类
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/Azure-Samples/art-voice-agent-accelerator --skill add-voice-handler命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
Read-only — assemble the wider runtime picture of a deployed voice app from azd deployment artifacts and Azure Monitor (Application Insights / Log Analytics) via Azure MCP or az CLI, then render it as KQL, call timelines, latency waterfalls, and mermaid diagrams
Service catalog and guided onboarding for the azd deployment. USE WHEN the user wants to discover, install, set up, or be walked through the deployable components (Azure OpenAI/AI Foundry, Speech, ACS/telephony, Cosmos DB, Redis, Container Apps, Key Vault, App Config, CardAPI MCP), asks "what gets deployed", "what services does this use", "help me onboard", "set up the deployment", "guide me through azd up", "which components do I need", or wants to enable optional pieces (phone number, EasyAuth, data seeding). Acts as the entry point an agent hooks into to assess current state, present the catalog, and onboard each component. DO NOT USE FOR: deep azd hook/flow internals or model-availability checks (use deployment-guide); runtime failure diagnosis (use troubleshoot); telemetry/log analysis (use observability-insights).
Agent-first, read-only diagnosis of the voice pipeline (deploy, telephony, STT, LLM, TTS, state) — gather evidence via Azure MCP / azd artifacts / CLI, probe the user for missing details, and recommend fixes without changing anything
| name | add-voice-handler |
| description | Add a new voice handler or feature to the voice module |
Add new voice features to apps/artagent/backend/voice/.
"""
Voice Feature Module
====================
Brief description of the voice feature.
"""
from __future__ import annotations
from typing import TYPE_CHECKING
from apps.artagent.backend.voice.shared.context import VoiceSessionContext, TransportType
from apps.artagent.backend.voice.shared.handoff_service import HandoffService
from apps.artagent.backend.voice.shared.metrics_factory import LazyMeter, build_session_attributes
from utils.ml_logging import get_logger
if TYPE_CHECKING:
from azure.cognitiveservices.speech import SpeechConfig
logger = get_logger(__name__)
# Lazy metrics
_meter = LazyMeter("voice.my_feature", version="1.0.0")
_latency = _meter.histogram(
name="voice.my_feature.latency",
description="Feature latency",
unit="ms",
)
async def handle_my_feature(
context: VoiceSessionContext,
data: bytes,
) -> None:
"""
Handle voice feature.
Args:
context: Voice session context (use instead of websocket.state)
data: Input data to process
"""
# Transport-aware processing
if context.transport_type == TransportType.BROWSER:
sample_rate = 48000
elif context.transport_type == TransportType.ACS:
sample_rate = 16000
else:
sample_rate = 24000 # VoiceLive
# Process and record metrics
attrs = build_session_attributes(context.session_id)
_latency.record(latency_ms, attributes=attrs)
voice/ or appropriate subdirectoryVoiceSessionContext instead of websocket.statevoice. prefixfrom apps.artagent.backend.voice.shared.context import VoiceSessionContext
context = VoiceSessionContext.from_websocket(websocket)
session_id = context.session_id
transport = context.transport_type
from apps.artagent.backend.voice.tts import TTSPlayback
tts = TTSPlayback(context)
await tts.speak(text) # Auto-routes to browser/ACS/VoiceLive
from apps.artagent.backend.voice.shared.handoff_service import HandoffService
handoff_service = HandoffService(
scenario_name=scenario_name,
handoff_map=handoff_map,
agents=agents,
memo_manager=memo_manager,
)
resolution = handoff_service.resolve_handoff(from_agent, to_agent)
from typing import TYPE_CHECKING
if TYPE_CHECKING:
from azure.cognitiveservices.speech import SpeechConfig
def create_speech_config() -> "SpeechConfig":
from azure.cognitiveservices.speech import SpeechConfig
return SpeechConfig(...)
VoiceSessionContext instead of websocket.stateTTSPlayback for audio outputLazyMeter pattern for metricsvoice. prefixSee voice-module.instructions.md for full patterns and contracts.