CCAO-F Prompting and Context Engineering Practice Question
A support team wants Claude to classify incoming tickets into exactly one of five categories and to always return the result as a JSON object with keys category and confidence. The developer has already written clear category definitions. Which additional step most directly improves the reliability of the JSON output?
⚠ Common exam trap
The trap here is reaching for chain-of-thought as a universal improvement, when adding a reasoning step can actually introduce prose that makes the structured output harder to parse.
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
✓
Add a short example showing a sample ticket and the exact JSON object Claude should return.
Demonstrating the exact output shape with a concrete example is the most direct way to lock down structured output. Category definitions establish what to decide; the example establishes how to present the decision. Together they leave little room for the model to improvise key names, wrap the object in prose, or choose an unexpected value format.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the maximum output tokens so the JSON object is never truncated.
Why it's wrong here
Truncation is not the reported problem, and a five-category classification with a confidence value is a very short response. Raising the output ceiling changes nothing about whether the model uses the right keys, values, or formatting. It addresses a failure mode that this scenario does not exhibit.
- ✗
Ask Claude to return the category and confidence as a plain sentence.
Why it's wrong here
A plain sentence contradicts the requirement for a JSON object with named keys. Downstream systems need machine-parseable fields, and free text would require additional extraction logic that reintroduces the ambiguity the team is trying to remove. This option moves away from the stated objective rather than toward it.
- ✓
Add a short example showing a sample ticket and the exact JSON object Claude should return.
Why this is correct
A single well-formed example demonstrates the exact schema, key names, and value formats expected, which is far more precise than describing the format in prose. Few-shot demonstration reduces variance in output shape, so the model reproduces the demonstrated structure rather than inventing its own keys or wrapping the JSON in commentary.
- ✗
Instruct Claude to 'think step by step' before producing the JSON object.
Why it's wrong here
Reasoning before answering can improve classification quality, but it also invites prose that may precede or wrap the JSON, complicating parsing. The stated goal is reliable structured output, and a demonstration of the exact object shape addresses that goal more directly than adding a reasoning step that changes the output surface.
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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 CCAO-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 CCAO-F exam.