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Anthropic CCAR-F Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Agentic Architecture & Orchestration | 27% | - Agentic loop design and stop_reason handling - Multi-agent patterns: coordinator-subagent and hub-and-spoke - Error recovery, guardrails and safety patterns - Task decomposition and dynamic subagent selection - Session state management and workflow enforcement |
| Topic 2: Tool Design & MCP Integration | 18% | - Tool distribution and permission controls - Error handling and tool response formatting - MCP tool, resource and prompt implementation - Tool schema design and interface boundaries - Model Context Protocol (MCP) architecture and JSON-RPC 2.0 |
| Topic 3: Prompt Engineering & Structured Output | 20% | - Validation, parsing and retry loop strategies - Explicit criteria definition and few-shot prompting - JSON schema design and structured output enforcement - System prompt design and persona alignment |
| Topic 4: Claude Code Configuration & Workflows | 20% | - Custom slash commands and plan mode vs direct execution - CLAUDE.md hierarchy, precedence and @import rules - Path-specific rules and .claude/rules/ configuration - CI/CD integration and non-interactive mode parameters - Hooks vs advisory instructions |
| Topic 5: Context Management & Reliability | 15% | - Token budget management and cost control - Context window optimization and prioritization - Context pruning and summarization strategies - Idempotency, consistency and failure resilience |
Anthropic Claude Certified Architect – Foundations Sample Questions:
1. 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) 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.
B) Run parallel worker agents that simultaneously investigate all four layers, then synthesize their findings to identify where the error originates.
C) Have the agent first create a comprehensive plan mapping all code paths through the endpoint before beginning any file exploration or code reading.
D) 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.
2. 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.
Your extraction system implements automatic retries when validation fails. On each retry, the specific validation error is appended to the prompt. This retry-with-error-feedback approach resolves most failures within 2-3 attempts.
For which failure pattern would additional retries be LEAST effective?
A) The model extracts citation counts as locale-formatted strings ("1,234") when the schema requires integers.
B) The model extracts dates as ISO 8601 datetime strings ("2023-03-15T00:00:00Z") when the schema requires only the date portion (YYYY-MM-DD).
C) The model extracts keywords as a nested object organized by category when the schema requires a flat array of strings.
D) The model extracts "et al." for co-authors when the full list exists only in an external document not in the input.
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.
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 with a summary of prior findings.
B) Launch a fresh subagent and include the prior transcript in the initial prompt for context.
C) Resume the subagent from its previous transcript without mentioning the changes-the architecture understanding remains valid.
D) Resume the subagent from its previous transcript and inform it about the renamed functions.
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.
You've asked Claude to write a data migration script, but the initial output doesn't correctly handle records with null values in required fields.
What's the most effective way to iterate toward a working solution?
A) Manually edit the generated code to fix the null handling, then continue working with Claude on other parts.
B) Provide a test case with example input containing null values and the expected output, then ask Claude to fix it.
C) Describe the null value problem in detail and ask Claude to regenerate the entire script with improved edge case handling.
D) Add "think harder about edge cases" to your prompt and request a complete rewrite of the migration logic.
5. 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 three requirements for Claude Code's behavior in your project:
* Claude must never modify files in the db/migrations/ directory.
* Claude should prefer your custom logging module over console.log .
* All TypeScript files must be auto-formatted with Prettier after every edit.
All three are currently written as instructions in your project's CLAUDE.md. During a complex refactoring session, a developer discovers that Claude edited a migration file, violating requirement #1.
How should you restructure these requirements across Claude Code's configuration mechanisms?
A) Add Edit(./db/migrations/**) to permissions.deny in the project settings, keep the logging preference in CLAUDE.md, and add a PostToolUse hook to run Prettier after TypeScript edits.
B) Move all three requirements into .claude/rules/ as path-scoped rules: one targeting db/migrations/** that forbids editing those files, and others targeting **/*.ts for the logging convention and formatting instruction.
C) Configure hooks for all three: a PreToolUse hook script that blocks Edit calls targeting db/migrations/ , a PreToolUse hook script that adds logging convention context before edits, and a PostToolUse hook that runs Prettier after TypeScript edits.
D) Rewrite all three requirements in CLAUDE.md using stronger directive language and add few-shot examples that demonstrate Claude refusing to edit migration files and running Prettier after edits.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: D | Question # 3 Answer: D | Question # 4 Answer: B | Question # 5 Answer: A |

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