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Updated: Jul 24, 2026

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Anthropic CCAR-F Exam Overview:

Certification Vendor:Anthropic
Exam Name:Claude Certified Architect – Foundations
Exam Number:CCA-F (also referred to as CCAR-F in some references)
Real Exam Qty:60
Passing Score:720 out of 1000 scaled score
Exam Duration:120 minutes
Exam Price:Free for first 5,000 partner employees during Early Access; $99 USD thereafter
Available Languages:English
Certificate Validity Period:2 years from date of passing
Exam Format:Multiple-choice single-select, Multiple-choice multiple-select, Scenario-based questions
Recommended Training:Anthropic Academy Official Training Courses
Exam Registration:Anthropic CCA-F Access Request & Registration
Anthropic Partner Network Application
Sample Questions:Anthropic CCAR-F Sample Questions
Exam Way:Online remotely proctored via ProctorFree; closed-book, no external resources allowed
Pre Condition:Currently restricted to employees of Anthropic Partner Network organizations. Recommended prerequisites: completion of all 200-level courses in Anthropic Academy, working familiarity with Claude Agent SDK, Claude Code, Anthropic API and Model Context Protocol (MCP), plus at least 6 months of hands-on experience building production solutions with Claude technologies.
Official Syllabus URL:https://anthropic.skilljar.com/claude-certified-architect-foundations-access-request

Anthropic CCAR-F Exam Syllabus Topics:

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

Anthropic Claude Certified Architect – Foundations Sample Questions:

1. 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 asked Claude Code to build a PDF report generation feature. The initial implementation queries the database correctly, but the output has formatting issues: table columns are too narrow causing content truncation, dates display without proper formatting, and page break handling is incorrect. You've noticed these issues interact-changing column widths affects how dates render, and page breaks depend on content height.
What's the most effective approach for iterating toward a working solution?

A) Provide all three issues in a single detailed message with exact specifications for each, allowing Claude to address them together in one update.
B) Address the column width issue first with specific measurements, verify it works, then fix date formatting within the corrected columns, then adjust page breaks-testing after each change.
C) Show Claude an example of a correctly formatted report and ask it to match that output, rather than listing the specific technical issues.
D) Start fresh with a detailed prompt specifying all formatting requirements upfront.


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 submits two requests:
* Request A: "Rename the getUserData function to fetchUserProfile everywhere it's used."
* Request B: "Improve error handling throughout the data processing module-add try/catch blocks, meaningful error messages, and ensure failures don't silently corrupt data." For which request does specifying an explicit multi-phase workflow (such as analyze # propose # implement with review) most improve outcome quality?

A) Neither request benefits significantly
B) Request A, the function rename task
C) Both requests benefit equally
D) Request B, the error handling task


3. 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 codebase exploration tool stores session IDs to allow engineers to continue investigations across work sessions. An engineer spent an hour yesterday analyzing a legacy authentication module, building context about its architecture and dependencies. They want to continue today. The session ID is valid, but version control shows 3 of the 12 files the agent previously read were modified overnight by a teammate's merge.
What approach best balances efficiency and accuracy?

A) Resume the session and inform the agent which specific files changed for targeted re-analysis
B) Resume the session without informing the agent about the changed files
C) Start a fresh session to ensure the agent works with current codebase state without stale assumptions
D) Resume the session and immediately have the agent re-read all 12 previously analyzed files


4. 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 wants Claude to follow a detailed code review checklist (8 items covering API changes, test coverage, documentation, security, etc.) when reviewing pull requests. The team also uses Claude extensively for other tasks: writing new features, debugging production issues, and generating documentation. Currently, developers paste the checklist at the start of each review session.
Which approach best addresses this workflow need?

A) Create a /review slash command containing the checklist, invoked when starting reviews.
B) Configure plan mode as the default for code review sessions.
C) Add the checklist to the project's CLAUDE.md file under a "Code Review" section.
D) Create a dedicated review subagent with the checklist embedded in its configuration.


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.
A developer asks the agent to investigate why a specific API endpoint intermittently returns 500 errors. The codebase has 200+ files and the developer doesn't know which components are involved. The agent must trace the error through routing, middleware, business logic, and database layers.
What task decomposition approach would be most effective?

A) Define a fixed sequence of investigation steps upfront-grep for error patterns, then read error handlers, then check database queries, then examine middleware-executing each step regardless of intermediate findings.
B) Have the agent dynamically generate investigation subtasks based on what it discovers at each step, adapting its exploration plan as new information about the error path emerges.
C) Run parallel worker agents that simultaneously investigate all four layers, then synthesize their findings to identify where the error originates.
D) Have the agent first create a comprehensive plan mapping all code paths through the endpoint before beginning any file exploration or code reading.


Solutions:

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

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