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AI-102 Practice Question: Implement knowledge mining and information extraction solutions
Which THREE components are required to build a custom skill for Azure AI Search enrichment?
⚠ Common exam trap
Candidates often think a custom skill requires an orchestration tool like Power Automate or a persistent storage layer, but Azure AI Search's enrichment pipeline handles orchestration natively and only needs a stateless HTTPS endpoint with a defined JSON schema.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
A web API endpoint that accepts JSON input and returns JSON output.
A custom skill in Azure AI Search must be implemented as a web API that receives a JSON payload containing the input fields defined in the skill's context and returns a JSON response with the output fields. This API is called by the AI Search enrichment pipeline during indexing, allowing you to inject custom logic (e.g., entity extraction, classification) into the skillset execution.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
A database to store intermediate results.
Why it's wrong here
Not required; results stored in enrichment cache.
- ✗
A Power Automate flow to orchestrate the skill.
Why it's wrong here
Not required.
- ✓
A web API endpoint that accepts JSON input and returns JSON output.
Why this is correct
Custom skill must be a web API.
- ✓
An HTTPS endpoint for the API.
Why this is correct
Azure AI Search requires HTTPS.
- ✓
A JSON schema defining inputs and outputs.
Why this is correct
Required for skill definition.
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