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Anthropic CCA-F Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Claude Code Configuration & Workflows | 20% | - Claude Code configuration
|
| Topic 2: Tool Design & MCP Integration | 18% | - Tool interface design
|
| Topic 3: Context Management & Reliability | 15% | - System reliability
|
| Topic 4: Agentic Architecture & Orchestration | 27% | - Multi-agent orchestration
|
| Topic 5: Prompt Engineering & Structured Output | 20% | - Instruction design
|
Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions:
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.
Your team has connected a custom MCP server that provides DevOps workflow templates. The server exposes several MCP prompts (such as deploy_checklist and incident_response) in addition to tools. How do these MCP prompts become accessible within Claude Code?
- A. They are surfaced as @-mentionable resources alongside files, fetched and attached to your message when referenced.
- B. They are automatically prepended to every conversation as additional system-level context, influencing Claude's behavior throughout the session.
- C. They appear as slash commands (e.g., mcp_servername_deploy_checklist) that you can invoke, with arguments passed after the command name.
- D. They are added to Claude Code's tool registry alongside the server's tools, invoked automatically by the model when relevant to the task.
Correct Answer: C 🗳️
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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. Run /memory to check which memory files are loaded and verify your CLAUDE.md is included.
- C. Search for conflicting instructions in ~/.claude/CLauDe.md or ~/.claude/rules/ that might override your project conventions.
- D. Create path-specific rules in .claude/rules/handlers.md with YAML frontmatter scoping the error handling instructions to your API handler files.
Correct Answer: B 🗳️
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A developer wants Claude to consistently answer as an experienced cybersecurity analyst regardless of the user question. Which prompt component should contain this instruction?
- A. User message
- B. System prompt
- C. Retrieved document
- D. Assistant response
Correct Answer: B 🗳️
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A developer wants Claude to explain every reasoning step internally before answering. Why might this request be inappropriate?
- A. Claude requires GPU acceleration.
- B. Temperature prevents explanations.
- C. Internal reasoning should not be relied upon as an application feature.
- D. JSON cannot contain reasoning.
Correct Answer: C 🗳️
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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. Expand MCP tool descriptions to detail capabilities and outputs - e.g., "Builds dependency graph showing direct imports, transitive dependencies, and cycles."
- 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. Remove Grep from available tools when the MCP server is connected to eliminate functional overlap.
- D. Add routing instructions to the system prompt specifying that dependency-related questions should use MCP tools rather than Grep.
Correct Answer: A 🗳️
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