Claude Certified Architect Foundations Practice Exams CCAR-F

Course Audit Trail

• August 2026 | Course Launched

  • This course is aligned with the Anthropic Claude Certified Architect – Foundations | Auguest 2026 Exam Version

  • Core Domains Covered :

    • 1. Agentic Architecture & Orchestration (Highest weight, ~27%)

    • 2. Tool Design & Model Context Protocol (MCP) Integration

    • 3. Claude Code Configuration & Workflows

    • 4. Prompt Engineering & Structured Output

    • 5. Context Management, Reliability, & Cost Optimization

  • The exam uses scenario-based questions. Each scenario presents a realistic production context thatframes a set of questions. During the exam, 4 scenarios are presented and picked at random from thefull set of the 6 scenarios below.

    • Scenario 1: Customer Support Resolution Agent

      • You are building a customer support resolution agent using the Claude Agent SDK. The agent handleshigh-ambiguity requests like returns, billing disputes, and account issues. It has access to yourbackend 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 whento escalate.

      • Primary domains: Agentic Architecture & Orchestration, Tool Design & MCP Integration, ContextManagement & Reliability

    • Scenario 2: Code Generation with Claude Code

      • 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 workflowwith custom slash commands, CLAUDE md configurations, and understand when to use plan mode vsdirect execution.

      • Primary domains: Claude Code Configuration & Workflows, Context Management & Reliability

    • Scenario 3: Multi-Agent Research System

      • You are building a multi-agent research system using the Claude Agent SDK. A coordinator agentdelegates to specialized subagents: one searches the web, one analyzes documents, one synthesizesfindings, and one generates reports. The system researches topics and produces comprehensive,cited reports.

      • Primary domains: Agentic Architecture & Orchestration, Tool Design & MCP Integration, ContextManagement & Reliability

    • Scenario 4: Developer Productivity with Claude

      • You are building developer productivity tools using the Claude Agent SDK. The agent helps engineersexplore unfamiliar codebases, understand legacy systems, generate boilerplate code, and automaterepetitive tasks. It uses the built-in tools (Read, Write, Bash, Grep, Glob) and integrates with ModelContext Protocol (MCP) servers.

      • Primary domains: Tool Design & MCP Integration, Claude Code Configuration & Workflows, AgenticArchitecture & Orchestration

    • Scenario 5: Claude Code for Continuous Integration

      • You are integrating Claude Code into your Continuous Integration/Continuous Deployment (CI/CD)pipeline. The system runs automated code reviews, generates test cases, and provides feedback onpull requests. You need to design prompts that provide actionable feedback and minimize falsepositives.

      • Primary domains: Claude Code Configuration & Workflows, Prompt Engineering & Structured Output

    • Scenario 6: Structured Data Extraction

      • You are building a structured data extraction system using Claude. The system extracts informationfrom unstructured documents, validates the output using JavaScript Object Notation (JSON)schemas, and maintains high accuracy. It must handle edge cases gracefully and integrate withdownstream systems.

      • Primary domains: Prompt Engineering & Structured Output, Context Management & Reliability

        Claude Certification Program

        Exam guide

Master Scenario-Based Decision-Making Across All Five CCAR-F Exam Domains

Every practice question is built around a realistic production context — customer support agents, multi-agent research pipelines, CI/CD code review, structured data extraction — and asks you to reason through tradeoffs the way a working Claude solution architect actually does, not just recall a definition.

Your practice questions are weighted to match the official exam blueprint, so your study time mirrors exactly where the real exam concentrates its points:

• Agentic Architecture & Orchestration (27%) — agentic loop control flow and stop_reason handling, coordinator/subagent orchestration, Task tool spawning, Agent SDK hooks (PostToolUse, tool call interception), session resumption and forking

• Claude Code Configuration & Workflows (20%) — CLAUDE md hierarchy and scoping, path-specific rules with glob patterns, custom slash commands and skills, plan mode vs. direct execution, CI/CD integration

• Prompt Engineering & Structured Output (20%) — few-shot prompting, tool_use with JSON schemas, validation-retry loops, batch processing tradeoffs, multi-pass review architectures

• Tool Design & MCP Integration (18%) — writing unambiguous MCP tool descriptions, structured error handling (isError, retryable flags), tool distribution across agents, MCP server scoping and resources

• Context Management & Reliability (15%) — preserving critical information across long sessions, escalation and ambiguity resolution, error propagation across multi-agent systems, confidence calibration, provenance tracking in multi-source synthesis

Six Scenarios, Zero Blind Spots

On exam day, CCAR-F randomly draws 4 of its 6 scenarios from the official scenario bank — meaning any scenario you haven't practiced is a real risk. This course covers all six, in depth:

• Customer Support Resolution Agent — identity verification enforcement, refund policy hooks, escalation calibration

• Code Generation with Claude Code — slash commands, CLAUDE md configuration, plan mode vs. direct execution

• Multi-Agent Research System — coordinator delegation, task decomposition, source provenance and conflict handling

• Developer Productivity with Claude — built-in tool selection (Read, Write, Edit, Bash, Grep, Glob), MCP server integration

• Claude Code for Continuous Integration — automated code review design, false-positive reduction, batch API tradeoffs

• Structured Data Extraction — JSON schema design, validation-retry loops, human review routing by confidence

Why This Course Is Built Differently

Most practice tests confirm the correct answer and move on. Every explanation in this course breaks down why each of the three wrong answers fails — because on the real exam, the wrong options are designed to look reasonable, and recognizing why they're wrong is the actual skill being tested. Questions are distributed to match the blueprint's exact domain weights rather than spread evenly, so your practice time reflects the real exam's point concentration. And because the official exam guide is a versioned document that Anthropic can revise, this course is revised alongside it — see the Course Update Log below for exactly what's changed and when.

What's Included

• Detailed, reasoning-based explanations for every question, covering why the correct answer is right and why each distractor falls short

• Questions calibrated to the same 100–1,000 scaled scoring model and 720 passing threshold used on the real CCAR-F exam

• Lifetime access

Who This Course Is For

• Solution architects and engineers preparing to sit the official Claude Certified Architect – Foundations (CCAR-F) exam

• Developers with hands-on experience building with the Claude Agent SDK, Claude Code, the Claude API, or Model Context Protocol (MCP) who want to pressure-test that knowledge before exam day

• Anyone who has completed Anthropic's official CCAR-F preparation material and wants realistic, scenario-based practice before scheduling their exam

A working familiarity with the Claude Agent SDK, Claude Code, and MCP is assumed. This is a practice-exam course, not an introductory course, and it closely follows the structure and weighting of the official Anthropic CCAR-F exam guide (v1.0, effective July 2026).

By the end of this course, you'll have reasoned through production-style architecture decisions across every domain and every scenario the real exam covers, know precisely which topics need more study time based on your own practice scores, and walk into exam day having already practiced the exact kind of tradeoff analysis CCAR-F is built to test.

This is an independent, unofficial practice-exam course. It is not affiliated with, endorsed by, or sponsored by Anthropic, and no content from the official proctored exam is reproduced here.

This course contains the use of artificial intelligence