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Exam Code: CCA-F

Exam Name: Claude Certified Architect - Foundations

Certification Provider: Anthropic

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"Claude Certified Architect - Foundations Exam", also known as CCA-F exam, is a Anthropic certification exam.

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Anthropic CCA-F Practice Test 3

Question 20

A tool call returns JSON that matches the extraction schema, but its invoice total is $430 while the extracted line items sum to $395. What must the application do before booking the invoice?

  1. Approve the invoice because strict tool-use JSON cannot contain semantic errors.
  2. Drop the stated_total field from output to avoid revealing the conflict.
  3. Round the line items until their sum matches the declared total.
  4. Perform a semantic total reconciliation and route the mismatch for correction or review even though the JSON is syntactically valid.

Explanation

Correct Answer

D:

Schema conformance guarantees shape, not mathematical truth. A separate calculation can detect inconsistent financial values that a JSON validator accepts.

Incorrect Answers

A:

Valid fields can still hold wrong numbers. Mathematical reconciliation is independent of JSON syntax and field-type checks.

B:

Hiding a mismatch removes important evidence. Preserving both computed and reported totals helps resolve a real data discrepancy.

C:

Arbitrary adjustment fabricates financial information. The pipeline must verify the source and explicitly handle the inconsistency.

Question 21

An extraction model outputs a valid-looking date but violates a required ISO format. The source document contains the exact date in an unambiguous field. Which retry strategy best targets the correctable failure?

  1. Send the original source, previous failed extraction and the specific date-format validation error into a bounded retry.
  2. Resend only “try again” without the document or prior error details.
  3. Invent a default date and mark it extracted with high confidence.
  4. Repeat the extraction indefinitely until a parseable string happens to appear.

Explanation

Correct Answer

A:

Error-aware feedback tells the model what to repair while preserving the original evidence. Retrying can help format mistakes when source data are actually available.

Incorrect Answers

B:

An unconstrained retry may reproduce the same issue or invent a replacement. Specific source and validation context make correction more reliable.

C:

Defaults must not masquerade as source-derived facts. The source already has a date, so the pipeline should correct its representation.

D:

Unlimited retries waste resources and can conceal persistent defects. A bounded, error-informed retry with review fallback is safer.

Question 22

A software organization needs a code gate to respond in seconds before merging a pull request, and also needs low-priority overnight analysis of thousands of historic files. What API allocation is appropriate?

  1. Run the pre-merge gate exclusively in a batch and assume it completes before the reviewer clicks merge.
  2. Run every overnight file analysis as a synchronous request solely because it uses the same model.
  3. Treat batch result order as identical to submission order and ignore custom_id.
  4. Use synchronous requests for the blocking gate and Message Batches for the latency-tolerant overnight workload.

Explanation

Correct Answer

D:

A pre-merge decision needs predictable prompt response timing, whereas batches trade turnaround guarantees for throughput and cost efficiency. Track batch results by custom_id.

Incorrect Answers

A:

Batch delivery is asynchronous and lacks an interactive latency SLA. A blocking decision cannot depend on timely batch completion.

B:

Bulk work does not require each result immediately. Synchronous-only design forgoes the batch workflow advantage without improving the overnight requirement.

C:

Asynchronous responses can arrive in a different order. Correlation by custom_id is needed to map analysis back to source files.

Question 23

A coding agent reviews its own newly written authentication module in the same long conversation and repeatedly misses a subtle authorization flaw. Which review setup most directly reduces that bias?

  1. Ask the original session to describe its own code in greater detail and accept its assessment.
  2. Send the reviewer the complete chain of reasoning that justified every code decision.
  3. Skip security review if unit tests compile successfully.
  4. Run a separate review instance supplied with the changed code and criteria, but not the generator’s prior reasoning conversation.

Explanation

Correct Answer

D:

An independent context is more likely to question generator assumptions. Focused review evidence can then be checked against tests and the actual diff.

Incorrect Answers

A:

More self-explanation preserves the assumptions that caused the mistake. It does not supply a fresh perspective on the implementation.

B:

Inheriting generator reasoning can anchor the reviewer to the same explanation. The new reviewer should see the artifact, requirements and evidence instead.

C:

Compilation and unit tests do not rule out all authorization defects. A separate focused review is a complementary check.

Question 24

A pipeline launches Claude Code for a pull-request summary, but the job hangs asking for interactive input and produces prose that downstream automation cannot parse. Which invocation design fits unattended CI?

  1. Launch an ordinary interactive session and rely on the runner to type replies automatically.
  2. Parse whichever natural-language paragraph resembles a JSON object.
  3. Disable logging and tests so the job can complete before it requires user input.
  4. Use the documented non-interactive print mode and structured JSON output settings, with explicit permissions and context.

Explanation

Correct Answer

D:

The -p mode avoids a normal interactive session. Machine-readable output and controlled tool permissions let the CI job process results without waiting for a human prompt.

Incorrect Answers

A:

An unattended runner may wait indefinitely for interactive approvals. CI needs a deliberate non-interactive contract instead of an implicit terminal conversation.

B:

Free-form text is an unstable automation interface. Request structured output and validate the returned schema rather than guessing from prose.

C:

Removing diagnostics does not solve a hanging interactive prompt and weakens auditability. The issue is how Claude Code is invoked in the pipeline.

Question 25

A support conversation has been compacted three times. The assistant now describes a $127.35 refund as “roughly a hundred dollars” and forgets the promised 14-day deadline. What design best prevents this drift?

  1. Summarize the amount as “small refund” so future context uses fewer tokens.
  2. Assume the user will repeat the amount whenever it becomes important.
  3. Move only the earliest and most recent messages into context and discard the case facts.
  4. Maintain a structured case-facts block with the exact amount, date, request status and customer expectations outside lossy summary prose.

Explanation

Correct Answer

D:

Exact transactional facts should survive compaction unchanged and be injected into relevant later turns. The model can summarize narrative context without rounding the contract.

Incorrect Answers

A:

Vague summaries lose the exact financial number and timing obligation. These details control correct follow-up decisions.

B:

The workflow should preserve already known information. Repeated questioning creates friction and can result in inconsistent case handling.

C:

Important details may live in the middle of the conversation. A structured fact block protects them from position and truncation effects.

Question 26

A customer writes “I want to speak with a person now; do not troubleshoot further.” The agent could probably solve the issue automatically. What should its escalation policy do?

  1. Pretend that a human has joined while continuing the conversation as the automated agent.
  2. Acknowledge the request and initiate the documented human handoff while conveying the current verified case details.
  3. Require three failed automated troubleshooting attempts before escalating.
  4. Estimate frustration from sentiment alone and ignore the explicit request if the sentiment score is low.

Explanation

Correct Answer

B:

An explicit human request is a sufficient escalation trigger. The agent should not override that preference based on its own confidence that automation could work.

Incorrect Answers

A:

Misrepresenting the transfer violates transparency and does not satisfy the requested contact. A real documented handoff is required.

C:

That rule disregards the customer’s direct instruction. It can also consume time while withholding a requested human option.

D:

Sentiment classification is an unreliable proxy for an unambiguous stated preference. Directly expressed intent should take precedence.

Question 27

A document-search subagent times out twice, then finds one useful document before a third source remains unavailable. The coordinator must decide whether to proceed with gaps. What should the subagent return?

  1. A single string “failed” that hides completed results and attempted recovery.
  2. A fully written synthesis claiming every source was inspected.
  3. An endless local retry loop that blocks the coordinator until all sources respond.
  4. The partial findings with source references, attempted queries, typed failure details and remaining coverage gaps.

Explanation

Correct Answer

D:

Structured propagation lets the coordinator distinguish usable evidence from missing material. It can retry selectively or disclose limitations without discarding completed work.

Incorrect Answers

A:

An opaque error prevents efficient follow-up and wastes already gathered evidence. The coordinator needs both results and failure context.

B:

Claiming complete coverage despite unavailable sources fabricates provenance. The partial success should be transparent about what could not be checked.

C:

Some failures cannot be resolved within a specialist’s scope. It should escalate unresolved gaps rather than trap the whole workflow.

Question 28

After exploring a large monorepo, a coding agent begins referring to imaginary module names because its context is full of stale file dumps. Which remedy most directly supports a reliable continuation?

  1. Ask the model to use typical names for modules it cannot recall.
  2. Delete the repository’s existing dependency metadata to simplify the project.
  3. Store a concise, source-linked scratchpad of confirmed modules, open questions and changed files, then resume with selective re-reading.
  4. Keep adding unfiltered full-file dumps to the same conversation until output length increases.

Explanation

Correct Answer

C:

Structured state persistence protects discovered facts across compaction. The agent can revisit relevant files rather than repeatedly using stale or invented patterns.

Incorrect Answers

A:

Guesses about source structure can cause incorrect edits. A saved and verified module map should ground later steps.

B:

Deleting metadata is unrelated to context capacity and harms project analysis. The needed fix is disciplined state retention and selective reading.

D:

More irrelevant content exacerbates context pressure and does not prioritize verified module facts. Targeted exploration is more reliable.

Question 29

A document-extraction service reports 97% overall accuracy but consistently misreads totals on handwritten forms. Human reviewers are scarce. How should the review policy be adjusted?

  1. Assume the overall 97% metric guarantees every field type meets the same accuracy.
  2. Have reviewers inspect only perfectly printed templates because they are faster to read.
  3. Calibrate field-level confidence against labeled examples and stratify ongoing samples by document type, especially handwritten totals.
  4. Route every extraction above 95% confidence directly to payment with no further sampling.

Explanation

Correct Answer

C:

Aggregate accuracy can conceal a failing segment. Field-specific validation and targeted human review allocate attention to the actual high-risk extraction family.

Incorrect Answers

A:

A global average does not measure performance for individual fields or source formats. The known failure mode requires separate monitoring.

B:

That prioritizes the lowest-risk documents and leaves the known high-error handwritten totals unchecked. Sampling should reflect error risk and coverage.

D:

Raw confidence is not necessarily calibrated. High-confidence errors on handwritten forms can still cause material financial mistakes.

Question 30

Two retrieval agents disagree about a supplier’s deployment date. An aggregator compresses both findings into “deployment occurred recently” and removes the document IDs. What output design best supports a defensible answer?

  1. Average the two calendar dates into a midpoint and report it as the documented deployment date.
  2. Attach source identifiers, dates and an uncertainty marker to each disputed claim, and present the contradiction for resolution.
  3. Choose whichever date appears first in the merged paragraph and omit the other.
  4. Remove all source references so the answer appears concise and confident.

Explanation

Correct Answer

B:

Claim-level provenance prevents a synthesis step from laundering conflict into a false definite fact. Reviewers can trace each date to its evidence and assess freshness.

Incorrect Answers

A:

A date average has no source support and invents an event time. Conflicting records require clarification, not arithmetic compromise.

C:

Response order does not establish evidence quality. Silencing a contradiction misleads the reader about uncertainty.

D:

Without attribution, downstream users cannot verify the competing dates. Concision should not erase the evidence required for auditability.

Claude Certified Architect - Foundations (CCA-F) Practice Tests