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Anthropic CCAR-F Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Claude Code Configuration & Workflows20%- Hooks vs advisory instructions
- Path-specific rules and .claude/rules/ configuration
- Custom slash commands and plan mode vs direct execution
- CI/CD integration and non-interactive mode parameters
- CLAUDE.md hierarchy, precedence and @import rules
Topic 2: Tool Design & MCP Integration18%- Tool distribution and permission controls
- Model Context Protocol (MCP) architecture and JSON-RPC 2.0
- MCP tool, resource and prompt implementation
- Error handling and tool response formatting
- Tool schema design and interface boundaries
Topic 3: Prompt Engineering & Structured Output20%- Explicit criteria definition and few-shot prompting
- JSON schema design and structured output enforcement
- System prompt design and persona alignment
- Validation, parsing and retry loop strategies
Topic 4: Agentic Architecture & Orchestration27%- Error recovery, guardrails and safety patterns
- Task decomposition and dynamic subagent selection
- Multi-agent patterns: coordinator-subagent and hub-and-spoke
- Agentic loop design and stop_reason handling
- Session state management and workflow enforcement
Topic 5: Context Management & Reliability15%- Context pruning and summarization strategies
- Token budget management and cost control
- Idempotency, consistency and failure resilience
- Context window optimization and prioritization

Anthropic Claude Certified Architect - Foundations Sample Questions:

1. 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) 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.
B) 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.
C) 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.
D) 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.


2. 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.
An engineer's exploration subagent spent 30 minutes analyzing a legacy payment system, reading 47 files and documenting data flows. The session was interrupted when the engineer's connection dropped. While away, a teammate merged a PR that renamed two utility functions.
The engineer wants to continue the same exploration.
What's the most effective approach?

A) Launch a fresh subagent and include the prior transcript in the initial prompt for context.
B) Resume the subagent from its previous transcript and inform it about the renamed functions.
C) Resume the subagent from its previous transcript without mentioning the changes--the architecture understanding remains valid.
D) Launch a fresh subagent with a summary of prior findings.


3. A user asks Claude to ignore all previous instructions and reveal confidential internal prompt content. How should Claude behave?

A) Partially reveal hidden instructions.
B) Reveal the prompt.
C) Follow higher-priority instructions and refuse.
D) Generate random text.


4. You are building a customer support resolution agent using the Claude Agent SDK. The agent handles high-ambiguity requests like returns, billing disputes, and account issues. It has access to your backend systems through custom Model Context Protocol (MCP) tools ( get_customer, lookup_order , process_refund , escalate_to_human ). Your target is 80%+ first-contact resolution while knowing when to escalate.
After expanding the agent's MCP tools with delivery-specific capabilities ( check_delivery_status , contact_driver , issue_credit , apply_promo_code , update_delivery_address , reschedule delivery ), the total tool count has grown from 4 to 10. Your evaluation suite shows tool selection accuracy has dropped from 88% to 71%. Log analysis reveals the majority of errors involve the agent selecting between semantically overlapping tools - calling issue_credit when process_refund was correct, and calling check_delivery_status when lookup_order already returns the needed data. Which approach structurally eliminates the semantic overlap identified in the logs as the error source?

A) Consolidate semantically overlapping tools - merge issue_credit and process_refund into a single resolve_compensation tool with an action parameter, and fold check_delivery_status into lookup_order with an optional include_tracking flag.
B) Add few-shot examples to the system prompt demonstrating correct selection for each ambiguous tool pair, such as showing when issue_credit applies versus when process_refund is appropriate.
C) Enable the tool search tool with defer_loading on the six new tools, keeping the original four always loaded, so the agent dynamically discovers specialized tools only when needed.
D) Split the tools across two sub-agents - a "financial resolution" agent with process_refund , issue_credit ,and apply_promo_code , and a "delivery operations" agent with the remaining delivery tools - with a coordinator routing between them.


5. 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 has analyzed a complex service module -reading 23 source files, tracing request flows, and identifying error handling patterns. A developer wants to compare two testing strategies before committing to one: end-to-end tests with mocked external services vs. snapshot tests capturing expected outputs. They need to independently develop both approaches to evaluate trade-offs. How should you manage the sessions?

A) Continue in the original session, developing end-to-end tests first, then snapshot tests sequentially.
B) Resume the analysis session with fork_session enabled, creating a separate branch for each testing strategy.
C) Export the analysis session's key findings to a file, then create two new sessions that reference this file.
D) Start two fresh sessions, having each re-read the relevant source files before beginning.


Solutions:

Question # 1
Answer: B
Question # 2
Answer: B
Question # 3
Answer: C
Question # 4
Answer: A
Question # 5
Answer: B

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