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Anthropic · CCAR-F

Course material

30 task statements across 5 domains. Each one covers what the blueprint expects you to know, what it expects you to be able to do, and the anti-patterns that turn up as distractors.

The CCAR-F blueprint: a 60-question scenario exam needing 720 of 1000 to pass, split across five weighted domains — Agentic Architecture & Orchestration 27%, Tool Design & MCP Integration 18%, Claude Code Configuration & Workflows 20%, Prompt Engineering & Structured Output 20%, and Context Management & Reliability 15%.Open full size
Where the marks are. Domain 1 alone is more than a quarter of the paper — worth knowing before you decide what to read twice.

Domains

  1. 01Agentic Architecture & Orchestration7 task statements
    27%
  2. 02Tool Design & MCP Integration5 task statements
    18%
  3. 03Claude Code Configuration & Workflows6 task statements
    20%
  4. 04Prompt Engineering & Structured Output6 task statements
    20%
  5. 05Context Management & Reliability6 task statements
    15%

Exam scenarios

Every question is framed by one of these. The real exam presents four of the six, picked at random.

Scenario 0140 questions

Customer Support Resolution Agent

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.

Scenario 0240 questions

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 workflow with custom slash commands, CLAUDE.md configurations, and understand when to use plan mode vs direct execution.

Scenario 0340 questions

Multi-Agent Research System

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.

Scenario 0440 questions

Developer Productivity with Claude

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.

Scenario 0540 questions

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 on pull requests. You need to design prompts that provide actionable feedback and minimize false positives.

Scenario 0640 questions

Structured Data Extraction

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

Read it, then sit it

Your results break down by task statement and link back to the section each question came from.

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