CCAO-F Claude Model Fundamentals Practice Question
A financial analyst uses Claude 3.5 Sonnet to extract line items from quarterly PDFs. They want the model to output only a JSON array without any conversational filler. Which feature should they configure to enforce this output format most reliably?
⚠ Common exam trap
The trap here is assuming that lowering temperature to 0 or raising max_tokens will make Claude output clean JSON, when only explicit formatting instructions in the system prompt reliably constrain structure.
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
✓
Use the system prompt to instruct 'Output only a valid JSON array with no other text.'
The system prompt is the primary control for persistent behavioral instructions, including strict output formatting. Telling Claude to return only a valid JSON array with no additional text directly shapes the response structure. Other parameters like max_tokens, temperature, and streaming influence length, randomness, and delivery, but not the format contract the analyst needs.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Use the system prompt to instruct 'Output only a valid JSON array with no other text.'
Why this is correct
System prompts are the correct mechanism to set persistent behavioral constraints, including output format. Instructing the model to emit only a JSON array without conversational filler directly addresses the requirement and is honored across turns. While no prompt guarantees perfect syntax, this is the most reliable native control for the described scenario.
- ✗
Set the temperature to 0.
Why it's wrong here
Temperature 0 makes sampling greedy and more deterministic, but it does not guarantee a specific output format. Claude can still emit natural-language preamble or trailing notes even at zero temperature. Determinism reduces variance in wording, not the structural template, so it is insufficient for reliable JSON extraction.
- ✗
Enable streaming responses.
Why it's wrong here
Streaming affects how tokens are delivered to the client, not the content or format the model produces. Enabling it may even complicate parsing because the JSON arrives in incremental chunks. It does nothing to suppress filler text or enforce a schema, so it is irrelevant to the formatting requirement.
- ✗
Increase the max_tokens parameter to 4096.
Why it's wrong here
Increasing max_tokens only raises the output length ceiling; it does not constrain the model to a JSON structure or prevent prose. The model may still prepend explanations or wrap the array in markdown fences, which breaks strict parsers. This parameter controls truncation, not formatting, so it fails to enforce the required schema.
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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
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