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Microsoft Developing AI Apps and Agents on Azure Sample Questions:

1. Hotspot Question
You have a Microsoft Foundry project that contains an agent.
The agent uses tools to retrieve internal content and call external APIs. The agent is configured to let the model decide when to call the tools.
You need to publish the agent for a compliance workflow. The solution must meet the following requirements:
- Each workflow run must include a retrieval step before generating a
response.
- Tool calls must authenticate by using the published agent's own
identity.
- Tool access must use an identity isolated from other project
resources.
- Tool access must use support audit tracing.
What should you do? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

2. You have a Microsoft Foundry project that contains a high-traffic agent.
After a recent update, operational costs increase significantly.
Monitoring confirms that the volume of user traffic to the agent remains unchanged.
You suspect that changes to the request or response characteristics are causing the increase.
You need to identify whether the additional costs are driven by the model input size, the model output size, or expanded tool usage.
Which observability capability should you use?

A) latency
B) evaluation metrics
C) run success rate
D) token usage

3. You have an application named App1 that uses Azure Speech in Foundry Tools to transcribe live calls.
Transcript segments often contain both English and Spanish. App1 sends each segment to Azure Translator in Foundry Tools to translate to another language.
Sometimes, mixed-language segments result in incomplete or incorrect translations.
You need to reduce translation errors. The solution must ensure that the entire transcript is translated successfully.
What should you do before sending the segments to Translator?

A) Enable automatic language detection for the translation request.
B) Use document translation to translate the entire transcript as a single document.
C) Specify English as the source language in the translation request for all the segments.
D) Split the mixed-language segments into single-language segments and translate each segment separately.

4. You have a Microsoft Foundry project that ingests scanned PDF invoices stored in Azure Blob Storage. Each invoice contains printed fine items and has a table-based layout.
Extracted results are stored as structured JSON and used as grounding data for an agent in a Retrieval Augmented Generation (RAG) solution.
You need to create a single analyzer that meets the following requirements:
- Extracts the invoice number, invoice date, vendor name, and total
amount across varying templates
- Returns confidence scores so that results with confidence below 0.80
can be routed for supervisor review
What should you use?

A) the Azure Content Understanding in Foundry Tools prebuilt-layout analyzer
B) the Azure Content Understanding in Foundry Tools prebuilt-documentSearch analyzer and search.score from the Azure AI Search results for routing
C) a Foundry agent that has groundedness guardrails enabled to extract invoice fields and confidence scores
D) a custom Azure Content Understanding in Foundry Tools analyzer that defines the required fields as the extracted fields and the returned confidence scores for routing

5. You configure Azure AI Content Safety to moderate user-uploaded images in a generative application. During testing, a colleague claims an image returned a Violence severity score of 3.
Why is this result impossible?

A) The image content model returns only severity values 0, 2, 4, and 6
B) Severity 3 is reserved for the Self-Harm category only
C) Image moderation always returns a binary blocked or allowed flag, never a severity
D) Content Safety does not moderate images, only text

Solutions: