CCDV-F Prompt and Context Engineering Practice Question
A developer wants to use Claude for a creative writing assistant that generates unpredictable and varied story ideas. Which parameter should they primarily adjust to achieve this?
⚠ Common exam trap
Candidates frequently confuse temperature with top-p or frequency penalties, incorrectly believing that increasing top-p is the primary way to increase randomness rather than adjusting the temperature parameter.
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
✓
Temperature, by increasing it toward 1.0.
Temperature is the primary parameter for controlling the randomness of the model's output. Higher values (up to 1.0) make the probability distribution of the next token flatter, allowing the model to choose less likely words, which results in more creative, varied, and sometimes surprising content, which is ideal for brainstorming and storytelling.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Max tokens, to ensure the stories are long enough to be creative.
Why it's wrong here
Max tokens only limits the length of the response; it does not influence the creativity or variety of the content itself. A long story can still be repetitive or predictable if the sampling parameters (like temperature) are set to favor only the most likely tokens during the generation.
- ✓
Temperature, by increasing it toward 1.0.
Why this is correct
Increasing temperature adds 'entropy' to the token selection process. This encourages the model to take more risks and explore diverse paths in its internal probability map. For creative tasks, this is the most effective way to prevent the model from falling into 'safe' or cliché response patterns.
- ✗
Stop sequences, to prevent the model from ending the story too early.
Why it's wrong here
Stop sequences are used to truncate generation, not to encourage variety. While they can be used to stop a story at a specific point, they have no impact on the internal creativity or the 'unpredictable' nature of the language used by the model during the generation of the text.
- ✗
System prompt, by adding more technical constraints to the writing style.
Why it's wrong here
Adding more constraints in the system prompt usually makes the model's output more focused and specific, which can actually decrease the variety of the output. While it can define a style, it is the temperature parameter that governs the randomness within that style to produce varied ideas.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Anthropic exam blueprint
This CCDV-F practice question is part of Courseiva's free Anthropic 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 CCDV-F exam.