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Anthropic CCA-F Exam Syllabus Topics:

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

1. A developer includes multiple unrelated tasks inside one extremely long prompt. What is the MOST likely outcome?

A) Faster inference.
B) Improved reasoning.
C) Reduced instruction clarity.
D) Increased prompt clarity.

2. An architect needs Claude to produce structured JSON that downstream software can parse automatically. Which prompting strategy is BEST?

A) Use multiple unrelated examples.
B) Explicitly specify the required JSON schema and formatting rules.
C) Ask Claude to "respond normally."
D) Increase maximum output tokens only.

3. The coordinator provides detailed step-by-step instructions to the web search subagent, specifying exact search queries, source priorities, and date filters. Production monitoring reveals three issues: (1) the subagent reports "insufficient results" rather than trying alternative approaches when pre-specified searches fail, (2) research quality drops for emerging topics that don't match expected patterns, and (3) the subagent rarely surfaces valuable tangential sources.
What's the most effective way to improve subagent adaptability?

A) Add explicit fallback directives to the detailed instructions: "If specified searches yield fewer than N results, attempt alternative query formulations before reporting failure."
B) Implement a topic classification step where the coordinator categorizes requests as "well-defined" or "exploratory" and uses different instruction styles for each category.
C) Specify research goals and quality criteria (coverage breadth, source diversity, recency) rather than procedural steps, letting the subagent determine its search strategy.
D) Remove procedural details entirely, delegating with simple goals like "research X thoroughly" and relying on the subagent's general capabilities.

4. An organization wants predictable outputs for automated invoice classification. Which API parameter should generally be LOWER?

A) Context window
B) Prompt length
C) Temperature
D) Max tokens

5. After integrating a local MCP server providing code analysis tools (analyze_dependencies, find_dead_code, calculate _complexity), you verify the server is healthy and tools appear in the tools/list response. However, you observe that the agent consistently uses Grep to search for import statements instead of calling analyze_dependencies -even when users explicitly ask about "code dependencies." Examining tool definitions reveals:
MCP: analyze_ dependencies - "Analyzes dependency graph"
Built-in: Grep - "Search file contents for a pattern using regular
expressions. Returns matching lines with line numbers and surrounding
context."
What's the most effective approach to improve the agent's selection of MCP tools?

A) Remove Grep from available tools when the MCP server is connected to eliminate functional overlap.
B) Split analyze_dependencies into granular tools ( list_imports, resolve_transitive_deps, detect_circular_deps) so each has a focused purpose less likely to overlap with Grep.
C) Expand MCP tool descriptions to detail capabilities and outputs - e.g., "Builds dependency graph showing direct imports, transitive dependencies, and cycles."
D) Add routing instructions to the system prompt specifying that dependency-related questions should use MCP tools rather than Grep.

Solutions: