Anthropic CCA-F Exam : Claude Certified Architect Foundations (CCA-F)

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Anthropic CCA-F Exam Syllabus Topics:

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

1. In production, final reports frequently contain claims without proper source attribution.
Investigation shows that while the web search and document analysis agents correctly attach citations to their outputs, the synthesis agent loses track of which sources support which conclusions when combining findings. What's the most effective architectural change?

A) Require all subagents to output structured claim-source mappings that the synthesis agent must preserve and merge when combining findings from multiple sources.
B) Have the coordinator inject source identifier prefixes into text before each handoff, then parse these prefixes at report generation to reconstruct citations.
C) Maintain complete transcripts of all subagent interactions and add a citation-resolution agent to analyze logs and determine attributions before report generation.
D) Add a verification step where the report generator uses semantic similarity matching against original sources to reconstruct which claims came from which documents.

2. Anthropic's tool use documentation states: "Write instructive error messages. Instead of generic errors like 'failed', include what went wrong and what Claude should try next." A billing dispute agent uses lookup_order, which catches all exceptions and returns a tool_result with is_error:
true and the message "Tool execution failed". Monitoring shows two failure modes: the agent retries the identical call until hitting the turn limit, or it immediately calls escalate_to_human without trying alternative tools. Which change follows the documented recommendation and gives Claude the information it needs to select the correct recovery action for each error type?

A) Implement retry logic with exponential backoff inside each tool implementation so transient errors are resolved transparently within the tool before any failure result is surfaced to Claude in the agentic loop.
B) Remove is_error: true and return the error details as normal tool content, so Claude reasons about the response as data rather than treating it as a flagged failure condition that biases retry behavior.
C) Return error-type-specific messages with is_error: true, e.g., "Order not found-try get_customer to search by phone" for data errors and "Database timeout (transient)-retry should succeed" for infrastructure errors.
D) Add an error classification step in the agentic loop that intercepts tool errors before Claude sees them, tags each as "retry," "try_alternative," or "escalate," and appends that recommendation to the tool result.

3. When implementing your lookup_order MCP tool, the backend sometimes returns errors (e.g.,
"Order not found" or temporary database failures). What is the correct pattern for communicating these errors back to the agent?

A) Log the error server-side and return an empty result to avoid confusing the model
B) Return the error message in the tool result content with the isError flag set to true
C) Return a success response with a "status" field indicating the error type
D) Throw an exception from the tool handler so the agent framework can catch and log it

4. You are building a multi-agent research system using the Claude Agent SDK. A coordinator agent delegates to specialized subagents: one searches the web, one analyzes documents, one synthesizes findings, and one generates reports. The system researches topics and produces comprehensive, cited reports.
A user is expanding the research system beyond its single web search agent by adding specialized data sources. They add a financial API agent that returns structured JSON with revenue, margins, and growth rates; a news monitoring agent that returns prose summaries of recent developments; and a patent analysis agent that returns structured lists of technology areas. The synthesis agent combines these into executive briefings. Currently, it converts everything to bullet points, causing financial comparisons to lose tabular clarity and news summaries to lose narrative flow. What change would most improve briefing quality?

A) Standardize all subagent outputs to JSON with fields for claim, evidence, source, and confidence
B) Update the synthesis agent to render each content type appropriately - financial data as tables, news as prose
C) Add a format conversion layer between subagents and synthesis that transforms all outputs to a common intermediate representation
D) Standardize all subagent outputs to prose summaries with inline citations

5. You are using Claude Code to accelerate software development. Your team uses it for code generation, refactoring, debugging, and documentation. You need to integrate it into your development workflow with custom slash commands, CLAUDE.md configurations, and understand when to use plan mode vs direct execution.
You've documented API error handling conventions in a CLAUDE.md file at your project root, specifying that endpoint handlers should use a custom ApiError class. After several sessions, you notice Claude Code sometimes follows these conventions and sometimes uses generic try/catch blocks with string messages. The inconsistency appears random across different coding sessions. What's the most efficient first diagnostic step?

A) Add a more detailed code examples to your CLAUDE.md showing the exact ApiError usage pattern for different endpoint types.
B) Search for conflicting instructions in ~/.claude/CLauDe.md or ~/.claude/rules/ that might override your project conventions.
C) Run /memory to check which memory files are loaded and verify your CLAUDE.md is included.
D) Create path-specific rules in .claude/rules/handlers.md with YAML frontmatter scoping the error handling instructions to your API handler files.

Solutions: