Azure Communication Callautomation Java
Azure Communication Callautomation Java is an data AI skill with a core value of Build call automation workflows with Azure Communication Services Call Automation Java SDK. It
helps developers solve real-world problems in the data domain, boosting
efficiency, automating repetitive tasks, and optimizing workflows.
Build call automation workflows with Azure Communication Services Call Automation Java SDK. Use when implementing IVR systems, call routing, call recording, DTMF recognition, text-to-speech, or AI-...
Quick Facts
mkdir -p ./skills/azure-communication-callautomation-java && curl -sfL https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/skills/azure-communication-callautomation-java/SKILL.md -o ./skills/azure-communication-callautomation-java/SKILL.mdRun in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# Azure Communication Call Automation (Java)
Build server-side call automation workflows including IVR systems, call routing, recording, and AI-powered interactions.
Installation
<dependency>
<groupId>com.azure</groupId>
<artifactId>azure-communication-callautomation</artifactId>
<version>1.6.0</version>
</dependency>Client Creation
import com.azure.communication.callautomation.CallAutomationClient;
import com.azure.communication.callautomation.CallAutomationClientBuilder;
import com.azure.identity.DefaultAzureCredentialBuilder;
// With DefaultAzureCredential
CallAutomationClient client = new CallAutomationClientBuilder()
.endpoint("https://<resource>.communication.azure.com")
.credential(new DefaultAzureCredentialBuilder().build())
.buildClient();
// With connection string
CallAutomationClient client = new CallAutomationClientBuilder()
.connectionString("<connection-string>")
.buildClient();Key Concepts
| Class | Purpose |
|-------|---------|
| `CallAutomationClient` | Make calls, answer/reject incoming calls, redirect calls |
| `CallConnection` | Actions in established calls (add participants, terminate) |
| `CallMedia` | Media operations (play audio, recognize DTMF/speech) |
| `CallRecording` | Start/stop/pause recording |
| `CallAutomationEventParser` | Parse webhook events from ACS |
Create Outbound Call
import com.azure.communication.callautomation.models.*;
import com.azure.communication.common.CommunicationUserIdentifier;
import com.azure.communication.common.PhoneNumberIdentifier;
// Call to PSTN number
PhoneNumberIdentifier target = new PhoneNumberIdentifier("+14255551234");
PhoneNumberIdentifier caller = new PhoneNumberIdentifier("+14255550100");
CreateCallOptions options = new CreateCallOptions(
new CommunicationUserIdentifier("<user-id>"), // Source
List.of(target)) // Targets
.setSourceCallerId(caller)
.setCallbackUrl("https://your-app.com/api/callbacks");
CreateCallResult result = client.createCall(options);
String callConnectionId = result.getCallConnectionProperties().getCallConnectionId();Answer Incoming Call
// From Event Grid webhook - IncomingCall event
String incomingCallContext = "<incoming-call-context-from-event>";
AnswerCallOptions options = new AnswerCallOptions(
incomingCallContext,
"https://your-app.com/api/callbacks");
AnswerCallResult result = client.answerCall(options);
CallConnection callConnection = result.getCallConnection();Play Audio (Text-to-Speech)
CallConnection callConnection = client.getCallConnection(callConnectionId);
CallMedia callMedia = callConnection.getCallMedia();
// Play text-to-speech
TextSource textSource = new TextSource()
.setText("Welcome to Contoso. Press 1 for sales, 2 for support.")
.setVoiceName("en-US-JennyNeural");
PlayOptions playOptions = new PlayOptions(
List.of(textSource),
List.of(new CommunicationUserIdentifier("<target-user>")));
callMedia.play(playOptions);
// Play audio file
FileSource fileSource = new FileSource()
.setUrl("https://storage.blob.core.windows.net/audio/greeting.wav");
callMedia.play(new PlayOptions(List.of(fileSource), List.of(target)));Recognize DTMF Input
// Recognize DTMF tones
DtmfTone stopTones = DtmfTone.POUND;
CallMediaRecognizeDtmfOptions recognizeOptions = new CallMediaRecognizeDtmfOptions(
new CommunicationUserIdentifier("<target-user>"),
5) // Max tones to collect
.setInterToneTimeout(Duration.ofSeconds(5))
.setStopTones(List.of(stopTones))
.setInitialSilenceTimeout(Duration.ofSeconds(15))
.setPlayPrompt(new TextSource().setText("Enter your account number followed by pound."));
callMedia.startRecognizing(recognizeOptions);Recognize Speech
// Speech recognition with AI
CallMediaRecognizeSpeechOptions speechOptions = new CallMediaRecognizeSpeechOptions(
new Comm🎯 Best For
- UI designers
- Product designers
- Claude users
- Data professionals
- Analytics teams
💡 Use Cases
- Generating component mockups
- Creating design system tokens
- Data pipeline auditing
- Query optimization
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Azure Communication Callautomation Java to Your Work
Provide context for your task — paste source material, describe your audience, or share existing work to guide the AI.
- 4
Review and Refine
Edit the AI output for accuracy, tone, and completeness. Add human insight where the AI lacks context.
❓ Frequently Asked Questions
Does this work with Figma?
Some design skills integrate with Figma plugins. Check the Works With section for supported tools.
How do I install Azure Communication Callautomation Java?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/azure-communication-callautomation-java/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Skipping usability testing
AI-generated designs should be validated with real users before development.
Ignoring data quality
AI analysis inherits all data quality issues — profile your data first.