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Anthropic CCA-F Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Context Management & Responsible AI	15%	- Safety and compliance 1. Constitutional AI principles 2. Refusal handling and risk mitigation - Context window optimization 1. Token management and truncation strategies 2. Context retention and summarization
Topic 2: Tool Design & MCP Integration	18%	- Model Context Protocol (MCP) 1. MCP server and client setup 2. Tools, resources, and prompts integration - Tool definition and best practices 1. Error handling and validation 2. Tool descriptions and selection logic
Topic 3: Agentic Architecture & Orchestration	27%	- Agent design patterns 1. Agent loops and control flow 2. Hub-and-spoke multi-agent systems - Anthropic Agent SDK usage 1. Task spawning and tool management 2. Session state and context handling
Topic 4: Claude Code Configuration & Workflows	20%	- CI/CD and development integration 1. Plan mode vs direct execution 2. Pipeline automation and review - Configuration files and structure 1. CLAUDE.md and rules system 2. Custom commands and workflows
Topic 5: Prompt Engineering & Structured Output	20%	- Advanced prompting techniques 1. System prompts and role framing 2. Few-shot and chain-of-thought prompting - Structured data generation 1. Output validation and reliability 2. JSON schema enforcement

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Anthropic Claude Certified Architect Foundations (CCA-F) Sample Questions (Q103-Q108):

NEW QUESTION # 103
Your order management system requires tools for three distinct operations: issuing refunds (requires amount and reason), canceling orders (requires reason), and requesting reshipments (requires shipping address). Each operation shares an order_id parameter but has different additional requirements. You notice during testing that with your current unified tool design, the agent frequently omits required parameters or includes irrelevant ones. What design change will most effectively improve parameter accuracy?

A. Keep one unified tool with all parameters marked optional, but add detailed few-shot examples in the system prompt showing correct parameter combinations for each operation type.
B. Split into three separate tools (issue_refund, cancel_order, request_reshipment), each defining only the parameters required for that specific operation.
C. Keep one unified tool but add JSON Schema if-then-else conditionals to enforce that parameters like amount are required only when the operation type is "refund".
D. Keep one unified tool with a nested operation_details object parameter whose internal structure varies by operation type, documented in the tool description.

Answer: B

Explanation:
Separate tools with operation-specific schemas make the required parameters clear and reduce ambiguity during tool selection. This improves parameter accuracy because each tool exposes only the fields needed for that exact action, such as refund amount and reason, cancellation reason, or reshipment address.

NEW QUESTION # 104
You need to create a reusable behavior for complex refactoring. To prevent the exploration noise from polluting the main session's context window, which configuration should you use in your SKILL. md?

A. Set isolation: true in the YAML frontmatter.
B. Use a standard custom command in . claude/commands/ instead of a skill.
C. Add the /compact command at the end of the skill's instructions.
D. Set context: fork in the YAML frontmatter.

Answer: D

Explanation:
The 'context: fork' frontmatter option runs the skill in an isolated sub-agent context. This allows it to perform verbose exploration without polluting the main conversation session. Regular commands run in the main context.

NEW QUESTION # 105
A pull request modifies 14 files across a application. A single-pass automated review produces superficial comments, misses obvious bugs, and provides contradictory feedback. How should the review architecture be redesigned to resolve this?

A. Require developers to manually split the PR into smaller submissions.
B. Run three independent reviews on the full PR and only flag issues that reach consensus.
C. Switch to a model with a larger context window to process all files simultaneously.
D. Split the review into focused passes: analyze each file individually for local issues, followed by a separate integration pass for cross-file data flow.

Answer: D

Explanation:
Splitting large code reviews into per-file local analysis passes plus a separate cross-file integration pass prevents attention dilution. Large context windows alone do not solve attention quality issues, and forcing consensus across multiple monolithic runs can suppress real bugs.

NEW QUESTION # 106
Why is configuring the exact same Claude session to review its newly generated pull request code considered an architectural anti- pattern?

A. It exceeds the maximum token limit for the context window during the generation phase.
B. The reviewer retains the reasoning context and assumptions from the generation phase, creating confirmation bias.
C. Tools invoked during the first pass are permanently locked and cannot be reused in the review pass.
D. The Message Batches API does not support multi-turn tool calling within a single request.

Answer: B

Explanation:
Same-session self-review is an anti-pattern because the model retains the context and reasoning from the generation phase, leading to a blind spot or confirmation bias. Independent review instances with fresh contexts are much more effective at objectively evaluating code.

NEW QUESTION # 107
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
1. Claude must never modify files in the db/migrations/ directory
2. Claude should prefer your custom logging module over console.log
3. 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 on the Edit tool that runs Prettier on changed TypeScript files.
B. 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.
C. 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.
D. 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.

Answer: A

Explanation:
Hard restrictions belong in permission controls, coding preferences belong in CLAUDE.md, and deterministic formatting belongs in an automated hook. Instructions alone cannot reliably prevent prohibited file edits.

NEW QUESTION # 108
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