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Anthropic CCAR-F Exam Syllabus Topics:

Anthropic Claude Certified Architect - Foundations Sample Questions:

Question 1

An application frequently repeats the same background instructions in every API request. What is a potential downside?

A. Higher token usage and cost.
B. Increased hallucinations only.
C. Reduced model capability.
D. Lower reliability.

Question 2

An enterprise wants Claude responses to remain professional across every interaction. Where should tone instructions primarily reside?

A. Retrieved documents
B. User prompt only
C. System prompt
D. API key description

Question 3

Production reviews reveal inconsistent handling of uncertainty in final reports. Sometimes conflicting subagent findings are synthesized into a single confident statement (losing nuance), while other times reports over-hedge with excessive qualifications (becoming unhelpful). When the web search agent returns "industry analysts estimate $50B market size (methodology varies)" and the document analysis agent returns "peer-reviewed study estimates $35B (±$7B, 95% CI)," the coordinator either picks one arbitrarily or produces vague statements like "the market may be
$35B-$50B depending on factors." What systematic approach best addresses this?

A. Implement a confidence calibration layer that normalizes subagent uncertainty expressions to standardized probability scores (0.0-1.0), then weight-average findings by their calibrated confidence.
B. Configure subagents to only report findings meeting a high-confidence threshold, filtering uncertain information before it reaches the coordinator.
C. Instruct the synthesis agent to structure reports with explicit sections distinguishing well- established findings from contested ones, preserving original source characterizations and methodological context.
D. Add a verification subagent that cross-references findings across sources, only passing claims to synthesis that are corroborated by at least two independent sources.

Question 4

Your pipeline runs:
PROMPT="You are a code reviewer."
PROMPT="$PROMPT Analyze the provided diff"
PROMPT="$PROMPT for bugs, security issues,"
PROMPT="$PROMPT and style violations."
claude -p \
--dangerously-skip-permissions \
--system-prompt "$PROMPT" < diff.txt
The reviews complete and return feedback, but Claude comments only on the piped diff--it never reads surrounding files in the checked-out repository to understand broader context, even when the diff modifies a function called by many other modules. Which change to the invocation will cause Claude to read related repository files while still applying your custom review instructions?

A. Remove --system-prompt entirely and place the review instructions in a root-level CLAUDE.md because --system-prompt is incompatible with tool use under -p.
B. Keep --system-prompt and add --allowedTools "Read, Glob, Grep" because non-interactive -p mode otherwise disables filesystem tools.
C. Stop piping the diff through standard input and embed it in the prompt string so Claude Code treats the invocation as an agentic session rather than a stream-processing operation.
D. Replace --system-prompt with --append-system-prompt so the review instructions are added to Claude Code's default prompt instead of overwriting its built-in file-reading and code-navigation guidance.

Question 5

After the web search agent finds 25 sources (120K tokens of raw content), the document analysis agent extracts key insights (15K tokens), and the synthesis agent produces a coherent narrative draft (3K tokens), the coordinator must pass context to the report generation agent for the final output with proper source citations. What context-passing strategy provides the best balance of completeness and efficiency?

A. Pass a condensed summary of all prior stages that preserves the main findings and attributes them to sources by name only.
B. Pass the synthesis draft along with a structured source index that maps key claims to their source URLs and relevant excerpts.
C. Pass the full accumulated context from all prior agents.
D. Pass only the synthesis draft and have a separate post-processing pipeline match claims to sources and insert citations after the report is generated.

Solutions: