- A
Set the system prompt to 'You are a code generator. Output only Python code. Do not include any explanations.' and the user message to 'Generate code for...'
This combination precisely constrains the output to only code.
- B
Use chain-of-thought prompting to reason about the code before writing it
Why wrong: Chain-of-thought would produce reasoning text, which is unwanted.
- C
Use a zero-shot prompt: 'Write Python code for the following task:'
Why wrong: Zero-shot may still produce explanations before or after the code.
- D
Set max tokens to a low value to limit output length
Why wrong: Limiting tokens may cut off the code itself and does not prevent explanations.
Question 196 of 991
1Z0-1127 Prompt Engineering Practice Question
This 1Z0-1127 practice question tests your understanding of prompt engineering. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A team is building a code generation assistant that should output Python code without any explanations. They want to ensure the model only returns the code block. Which prompt strategy is MOST effective?
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
✓
Set the system prompt to 'You are a code generator. Output only Python code. Do not include any explanations.' and the user message to 'Generate code for...'
Option A is correct because setting the system prompt to explicitly instruct the model to output only Python code without explanations directly enforces the desired behavior at the highest priority level of the prompt hierarchy. This approach leverages the system prompt's role as a persistent instruction that overrides user messages, ensuring the model strictly returns code blocks without extraneous text.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Set the system prompt to 'You are a code generator. Output only Python code. Do not include any explanations.' and the user message to 'Generate code for...'
Why this is correct
This combination precisely constrains the output to only code.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use chain-of-thought prompting to reason about the code before writing it
Why it's wrong here
Chain-of-thought would produce reasoning text, which is unwanted.
- ✗
Use a zero-shot prompt: 'Write Python code for the following task:'
Why it's wrong here
Zero-shot may still produce explanations before or after the code.
- ✗
Set max tokens to a low value to limit output length
Why it's wrong here
Limiting tokens may cut off the code itself and does not prevent explanations.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the misconception that limiting output length (max tokens) or using zero-shot prompts is sufficient to control output format, when in fact only explicit system-level instructions reliably enforce content restrictions like 'code only'.
Detailed technical explanation
How to think about this question
Under the hood, the system prompt in models like GPT-4 or Claude acts as a meta-instruction that is prepended to the conversation and has higher weight than user messages in guiding behavior. In real-world deployments for code generation APIs, combining a strict system prompt with a user message that specifies the task (e.g., 'Generate Python code for a function that sorts a list') ensures the model adheres to formatting constraints without needing post-processing. A subtle behavior is that even with a strict system prompt, the model may occasionally output markdown code fences or brief comments unless explicitly forbidden, so adding 'Do not include markdown or comments' further tightens control.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the 1Z0-1127 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this 1Z0-1127 question test?
Prompt Engineering — This question tests Prompt Engineering — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Set the system prompt to 'You are a code generator. Output only Python code. Do not include any explanations.' and the user message to 'Generate code for...' — Option A is correct because setting the system prompt to explicitly instruct the model to output only Python code without explanations directly enforces the desired behavior at the highest priority level of the prompt hierarchy. This approach leverages the system prompt's role as a persistent instruction that overrides user messages, ensuring the model strictly returns code blocks without extraneous text.
What should I do if I get this 1Z0-1127 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
This 1Z0-1127 practice question is part of Courseiva's free Oracle 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 1Z0-1127 exam.
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