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Anthropic CCAR-F Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Prompt Engineering & Structured Output	20%	- Structured output generation and validation - Improving Claude response quality and consistency - Prompt design strategies
Topic 2: Context Management & Reliability	15%	- Evaluation and reliability strategies - Managing context windows and information flow - Production deployment considerations
Topic 3: Agentic Architecture & Orchestration	27%	- Agent coordination and orchestration patterns - Designing agentic systems and workflows - Selecting appropriate Claude architectures
Topic 4: Tool Design & MCP Integration	18%	- Designing effective tools for Claude applications - Model Context Protocol (MCP) concepts and integration - Tool safety, reliability, and usability
Topic 5: Claude Code Configuration & Workflows	20%	- Claude Code usage and configuration - Developer productivity workflows - Integrating Claude Code into development processes

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Anthropic Claude Certified Architect - Foundations Sample Questions (Q94-Q99):

NEW QUESTION # 94
The coordinator provides detailed step-by-step instructions to the web search subagent, specifying exact search queries, source priorities, and date filters. Production monitoring reveals three issues: (1) the subagent reports "insufficient results" rather than trying alternative approaches when pre-specified searches fail, (2) research quality drops for emerging topics that don't match expected patterns, and (3) the subagent rarely surfaces valuable tangential sources.
What's the most effective way to improve subagent adaptability?

A. Specify research goals and quality criteria (coverage breadth, source diversity, recency) rather than procedural steps, letting the subagent determine its search strategy.
B. Add explicit fallback directives to the detailed instructions: "If specified searches yield fewer than N results, attempt alternative query formulations before reporting failure."
C. Remove procedural details entirely, delegating with simple goals like "research X thoroughly" and relying on the subagent's general capabilities.
D. Implement a topic classification step where the coordinator categorizes requests as "well-defined" or "exploratory" and uses different instruction styles for each category.

Answer: A

Explanation:
Delegating goals and quality criteria gives the subagent room to adapt its strategy while still defining what good research looks like. This improves handling of failed searches, emerging topics, and useful tangential sources because the subagent can vary queries, sources, and filters to satisfy the research objective rather than rigidly following preset steps.

NEW QUESTION # 95
A customer returns 4 hours after the initial session about the same billing dispute. The previous
32-turn session contains lookup_order results showing "Status: PENDING, Expected resolution:
24-48 hours." In testing, you observe that when resuming sessions with stale tool results, the agent often references the outdated data in responses (e.g., "I see your refund is still being processed") even after subsequent fresh tool calls return different information. What approach most reliably handles returning customers?

A. Resume with full history and configure the agent to automatically re-call all previously-used tools at session start to ensure data freshness.
B. Start a new session, inject a structured summary of the previous interaction (issue type, actions taken, resolution status), then make fresh tool calls before engaging.
C. Resume with full history but filter out previous tool_result messages before resuming, keeping only the human/assistant turns so the agent must re-fetch needed data.
D. Resume with full history and add a system prompt instruction telling the agent to always prefer the most recent tool results when multiple calls to the same tool exist in context.

Answer: B

Explanation:
Providing a concise structured summary preserves essential context from the previous session while ensuring the agent retrieves fresh, up-to-date tool results. This prevents reliance on stale data and allows accurate, current responses to the returning customer.

NEW QUESTION # 96
Which statement BEST describes Retrieval-Augmented Generation?

A. It compresses model weights.
B. It permanently retrains Claude.
C. It changes token pricing.
D. It supplies relevant external knowledge during inference.

Answer: D

NEW QUESTION # 97
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. 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.
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. 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.

Answer: A

Explanation:
Each requirement belongs in the mechanism matching its enforcement semantics. The migration restriction is a hard safety boundary, so it should be implemented through permissions.deny , not merely expressed as contextual guidance. Anthropic explicitly states that CLAUDE.md content is treated as context rather than enforced configuration. Permission rules use the Tool(specifier) form, evaluate deny rules before ask or allow rules, and support path-based Edit(...) restrictions. ( https://code.claude.com/docs/en/memory ) The custom logging convention is a persistent project preference, making CLAUDE.md the appropriate location. It should guide Claude's code-generation decisions but does not require deterministic interception.
Prettier formatting, by contrast, is deterministic automation. Anthropic documents the exact pattern of using a PostToolUse hook with an Edit|Write matcher to run Prettier automatically after file modifications. (
https://code.claude.com/docs/en/hooks-guide )
Option A incorrectly treats path-scoped rules as a security control; rules remain instructions. Option B overuses hooks for a semantic coding preference that belongs in CLAUDE.md. Option C relies entirely on stronger prompting, which cannot guarantee that protected files remain untouched. Option D correctly separates prohibition, preference, and automatic enforcement.
Official references/topics: Permission rules, CLAUDE.md semantics, PostToolUse formatting hooks.

NEW QUESTION # 98
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're implementing a complex graph traversal algorithm with specific performance requirements and edge cases to handle (disconnected nodes, cycles, weighted edges). You want to structure your workflow for efficient iterative refinement with Claude. What approach will most effectively enable progressive improvement across multiple iterations?

A. Provide Claude with a reference implementation from documentation, then ask it to rewrite the code to match your codebase style and add the required edge case handling, comparing outputs against the reference.
B. Write a test suite covering expected behavior, edge cases, and performance requirements before implementation. Ask Claude to write code that passes the tests, then iterate by sharing test failures with each refinement request.
C. Have Claude extensively research the algorithm and create a detailed implementation plan using extended thinking, then implement the complete solution based on that plan.
D. Provide Claude with a detailed natural language specification of the algorithm, including all requirements and edge cases. Review each output manually and provide descriptive feedback on what behavior needs to change.

Answer: B

Explanation:
Tests provide an executable specification and objective feedback for each iteration. Claude can implement against the suite, run it, inspect failures, and progressively refine the algorithm until correctness and performance requirements are met. Anthropic recommends running tests and fixing failures as an iterative Claude Code workflow.

NEW QUESTION # 99
......

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