CCAR-F Agentic Architecture and Orchestration Practice Question
A research agent must answer questions that require looking up several unrelated facts, such as the population of three different cities. The architect observes that Claude frequently emits one search tool call, waits for the result, then emits the next, repeating until all facts are gathered. This serial pattern roughly triples latency versus what the workload should allow. Which change most directly enables the model to request all three independent lookups in a single assistant turn?
⚠ Common exam trap
The trap here is assuming a parameter or larger token budget will force parallel tool calls, when parallelization is influenced by prompting and by how the client batches results.
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 system instruction that encourages Claude to batch independent lookups by requesting multiple tool calls in the same turn when the queries do not depend on each other.
Parallel tool use is a capability the model exercises when the calls are independent, and explicit guidance in the system prompt reliably encourages it. The client executes the returned tool_use blocks concurrently and submits all tool_result blocks together, cutting three sequential round trips down to one. No API parameter forces this; it is a prompting and orchestration practice.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Switch the search tool from a single-query parameter to an array parameter so one call can carry all three queries.
Why it's wrong here
Redesigning the tool is a valid optimization in some systems, but it changes the tool contract and requires matching client-side execution logic; it does not by itself make Claude parallelize independent tools. The question targets the model's tendency to serialize calls, which is a planning behavior.
- ✗
Set tool_choice to force a specific search tool on every turn so the model cannot choose to wait between calls.
Why it's wrong here
Forcing a particular tool constrains which tool is used, not how many calls appear in a turn, and it can prevent the model from producing a final answer. It does not eliminate the wait-for-result pattern that produces the serial latency.
- ✗
Increase max_tokens so the model has room to write more tool_use blocks before the response is truncated.
Why it's wrong here
Truncation is not the constraint here; the model is deliberately calling one tool at a time. Raising max_tokens only permits longer output and does not change the planning behavior that causes the serial round trips, so latency would remain roughly the same.
- ✓
Add a system instruction that encourages Claude to batch independent lookups by requesting multiple tool calls in the same turn when the queries do not depend on each other.
Why this is correct
Claude can already emit several tool_use blocks in one assistant turn; the serial behavior is a planning choice, and prompt-level guidance to parallelize independent calls is the direct, low-cost lever. This preserves the single conversation while collapsing three dependent round trips into one.
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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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