AI-102 Implement agentic AI solutions Practice Question
An agent uses Azure OpenAI with function calling to perform actions. The agent is not executing functions correctly. Which THREE factors should the team check to diagnose the issue?
⚠ Common exam trap
Microsoft often tests the misconception that temperature or model version are primary causes for function-calling failures, when in reality the core issues are token limits, schema correctness, and description clarity.
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
✓
The token limit is too low, truncating the function definitions.
Option B is correct because function definitions are serialized into the prompt sent to the model, so if the token limit (max_tokens/context window) is too low, the function schema can be truncated and the model cannot emit valid function calls. Option C is correct because Azure OpenAI function calling relies on a strict JSON Schema for each function's parameters; incorrect or incomplete schemas (wrong types, missing required fields) cause the model to produce arguments that fail validation or the call to be rejected. Option D is correct because the model selects functions based on their natural-language descriptions, so ambiguous or missing descriptions lead to wrong or no function selection. Option A is not a primary cause: temperature affects randomness, not whether a syntactically valid function call is produced, and function calling can work at high temperature. Option E is not a required check: while newer models may improve function-calling reliability, an outdated model version is not a standard diagnostic factor for functions failing to execute.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The temperature parameter is set too high.
Why it's wrong here
Temperature controls randomness of generated text, not whether the model emits valid function-call arguments or the runtime executes them. It tempts because high values cause erratic output, but function execution failures usually trace to schema definitions, tool registration or prompt instructions, which temperature does not govern.
- ✓
The token limit is too low, truncating the function definitions.
Why this is correct
Function definitions consume prompt tokens alongside the conversation. If the model's context window or max token setting is too low, definitions get truncated, so the model receives incomplete schemas and cannot emit valid function call arguments, causing execution failures.
- ✓
The function parameter schemas are incorrect or incomplete.
Why this is correct
The model generates function call arguments by reading the declared JSON schema. Malformed types, missing required fields, or incorrect parameter names cause the emitted arguments to fail validation against the actual function, so the call never executes correctly.
- ✓
The function descriptions are ambiguous or missing.
Why this is correct
The model selects which function to invoke based on the natural-language description. Ambiguous or absent descriptions leave the model unable to match user intent to the correct function, so it either skips the call or invokes the wrong one.
- ✗
The model version is outdated.
Why it's wrong here
Model version does not govern function-calling execution; the schema, tool definitions and response handling do. An outdated model may still invoke functions correctly. Upgrading is relevant when a newer model adds capabilities such as parallel tool calls, not when calls fail to execute.
Go deeper
Related to this question
About these practice questions
Courseiva writes every AI-102 question from scratch — 761 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-102 practice question is part of Courseiva's free Microsoft certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI-102 exam.