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Anthropic CCA-F Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Agentic Architecture & Orchestration	27%	- System orchestration patterns 1. Hub-and-spoke agent systems 2. Task decomposition strategies - Agentic loop design and execution lifecycle 1. Multi-agent coordination and delegation patterns 2. Tool use decision flow (tool_use vs end_turn)
Topic 2: Context Management & Reliability	15%	- Long-context optimization 1. Context window management 2. Reliability and retry strategies
Topic 3: Prompt Engineering & Structured Output	20%	- Reliable structured generation 1. Schema-guided outputs 2. Prompt patterns for agents
Topic 4: Tool Design & MCP Integration	18%	- Model Context Protocol (MCP) 1. MCP client/server integration patterns 2. Tool schema design
Topic 5: Claude Code Workflows & Configuration	20%	- Claude Code operational patterns 1. CI/CD and workflow integration 2. Plan mode vs execution mode

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Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions (Q97-Q102):

NEW QUESTION # 97
Users report that final reports sometimes lack depth on specific subtopics. Investigation shows that the document analysis agent frequently identifies gaps - for instance, noting "the retrieved sources discuss API authentication but lack details on token refresh patterns" - but under the current strict pipeline, this insight isn't actionable since search has already completed. What's the most effective architectural change?

A. Add a research planning agent before the search phase that decomposes topics into specific sub- questions.
B. Have the coordinator review analysis output for gap indicators and re-invoke search with gap- informed queries when gaps are detected.
C. Have the synthesis agent attach confidence scores to each section and flag areas with insufficient coverage for manual review.
D. Have the analysis agent report specific gaps to the coordinator, which triggers targeted searches and re-invokes analysis until sufficient.

Answer: B

Explanation:
Making the coordinator gap-aware allows it to dynamically re-delegate targeted searches based on analysis feedback. This iterative loop ensures subtopics with insufficient coverage are addressed before synthesis, improving the depth and completeness of final reports.

NEW QUESTION # 98
Your MCP server includes archive_file(file_id) and delete_file(file_id) tools. Production logs show the agent calls delete_file when users ask to "remove old backups," but company policy requires archiving backup files. Both tools currently have minimal descriptions: "Archives a file" and
"Deletes a file." Which change most directly improves tool selection for this scenario?

A. Expand tool descriptions to clarify use cases, adding guidance like "Do not use for backup files" to delete_file.
B. Implement server-side validation that rejects delete_file calls for files tagged as backups, returning an error message suggesting archive_file.
C. Add a confirmation step that requires users to type "CONFIRM DELETE" before delete_file executes.
D. Add few-shot examples to the system prompt demonstrating that requests involving "backup" or
"old" should use archive_file.

Answer: A

Explanation:
Clear tool descriptions directly guide the agent's choice between similar tools. Adding use-case guidance that backup files should not be deleted and should be archived helps the agent map
"remove old backups" to the correct archive operation before execution.

NEW QUESTION # 99
Production logs reveal inconsistent error handling: when lookup_order fails, the agent sometimes retries 5+ times (wasteful when the order ID doesn't exist), sometimes escalates immediately (premature for temporary network issues), and sometimes asks users for clarification (inappropriate when the issue is a backend permission error). Investigation shows your MCP tool returns uniform error responses: {"isError": true, "content": [{"type": "text", "text": "Operation failed"}]}. The agent cannot distinguish between error types. What's the most effective improvement?

A. Enhance error responses with structured metadata: include errorCategory (transient/validation/permission), isRetryable boolean, and a description of what caused the failure.
B. Implement retry logic with exponential backoff in your MCP server for all errors, returning to the agent only after retries are exhausted.
C. Add few-shot examples to the system prompt demonstrating how to interpret error message patterns and select appropriate responses for each.
D. Create an analyze_error MCP tool the agent calls after any failure to determine the error category and recommended action.

Answer: A

NEW QUESTION # 100
You are building developer productivity tools using the Claude Agent SDK. The agent helps engineers explore unfamiliar codebases, understand legacy systems, generate boilerplate code, and automate repetitive tasks. It uses the built-in tools (Read, Write, Bash, Grep, Glob) and integrates with Model Context Protocol (MCP) servers.
Your agent needs to insert a new helper function into the middle of a 150-line utility module, between two existing functions. The Edit tool fails because its old_string parameter cannot find unique text to match - the file has repetitive docstrings, variable names, and structural patterns.
What's the most reliable way to complete this insertion?

A. Use Bash to append the function definition to the end of the file using heredoc syntax
B. Use Read to load the file, add the function at the appropriate location, then Write the updated file
C. Use Edit's replace_all parameter to target a common pattern and embed the new function in the replacement text
D. Use Edit with an extremely long old_string capturing 30+ lines of context to guarantee uniqueness

Answer: B

Explanation:
When Edit cannot identify a unique match, rewriting the fully read file is the most reliable way to control the exact insertion point. The other options are brittle, place the function incorrectly, or risk unintended replacements.

NEW QUESTION # 101
A application features a tool designed to fetch a user's profile. During execution, the tool fails to connect to the database due to a timeout. Why is silently returning an empty array [ ] in this scenario considered a catastrophic anti-pattern?

A. It causes the agent to misinterpret an access failure (could not check) as a valid empty result, wrongly concluding the user does not exist.
B. It causes the Claude API to throw a 400 Bad Request error due to missing required schema fields.
C. It forces the model to ignore all subsequent tool calls in the session.
D. It prevents the use of few-shot prompting in the next iteration.

Answer: A

Explanation:
Access failures (e.g., database down, timeout) must be explicitly distinguished from empty results (e.g., checked database, found zero matches). Silently returning an empty array for an access failure misleads the agent into believing the data does not exist, leading to completely incorrect assumptions.

NEW QUESTION # 102
......

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