Anthropic CCA-F Exam Dumps

Question # 1

A developer's agent needs to process CSV files uploaded by users. The files vary from 100 rows to 1million rows. For small files, direct context inclusion works well. For large files, the context can't holdall data. What scalable architecture handles both cases?

A. Always process the full CSV regardless of size, relying on compaction if needed 
B. Always chunk the CSV into 100-row segments and process sequentially 
C. For small files (<5K rows): include directly in context. For large files: load into a database and provide SQL query tools for the agent to explore the data on demand
D. Convert all CSVs to summary statistics before processing 

  Show Answer

Question # 2

A development team is implementing context awareness (citations) for a RAG application. They wantto display inline citations like 'According to [Source A], the market grew by 15%.' The API returnscitation objects with character-level indices. How should the client render these?

A. Use the citation indices to insert reference markers into the text, linking each marker back to the specific passage in the source document
B. Append all citations as footnotes at the end of the response 
C. All of the above are valid rendering approaches depending on UX requirements
D. Create a sidebar with source highlights that appear when hovering over cited text 

  Show Answer

Question # 3

A team is evaluating their Claude Code setup and wants to understand the permission model. They adda new tool via MCP that can execute shell commands. When an agent tries to use this tool, it gets apermission error. Where are MCP tool permissions managed?

A. In .claude/settings.json under the 'allowedTools' and 'blockedTools' arrays, with glob pattern matching for MCP tool names
B. In the CLAUDE.md file under an 'allowed_tools' section 
C. In the MCP server configuration file 
D. Permissions are managed per-conversation and reset each time 

  Show Answer

Question # 4

A developer builds an MCP server that provides a search tool. The search tool returns results withURLs. After deployment, they notice Claude sometimes fabricates URLs that look similar to realresults but don't exist. What server-side measures prevent this?

A. Add URL validation in the system prompt instructing Claude to only use URLs from tool results 
B. Use context awareness (citations) to track which URLs come from tool results vs. model generation
C. Implement client-side URL validation that checks all URLs in Claude's response 
D. Return URLs as structured data in tool results (not embedded in text) and instruct Claude to reference results by ID rather than regenerating URLs

  Show Answer

Question # 5

A product team is designing a fraud detection agent for a bank. The agent analyzes transactions in realtime and flags suspicious activity. False positives block legitimate transactions, causing customerfrustration. False negatives allow fraud through. Currently the agent flags 30% of transactions, ofwhich 90% are false positives. What analysis framework should be applied?

A. Lower the sensitivity threshold to reduce false positives 
B. Use a tiered confidence system: high-confidence fraud ? block immediately, medium-confidence? add friction (2FA), low-confidence ? allow with monitoring. Each tier has different precision/recalltradeoffs
C. Remove automated blocking entirely and rely on post-transaction review 
D. Train a separate classifier to pre-filter the agent's results 

  Show Answer

Question # 6

A developer notices that their Claude Code session becomes sluggish after extended use. Responsestake longer and quality decreases. They suspect context window saturation. What is the recommendedmaintenance approach for long coding sessions?

A. Restart Claude Code to get a fresh context window
B. Delete all CLAUDE.md files temporarily to reduce context consumption 
C. Use /compact to manually trigger compaction, then verify Claude's understanding of the current task by asking it to summarize what it knows 
D. Switch to a model with a larger context window 

  Show Answer

Question # 7

A DevOps engineer is building an agent that must generate responses in strict compliance with acompany's brand voice guide (a 15-page document). They've included the full brand guide in thesystem prompt. Responses generally match the brand voice, but occasionally Claude generates offbrand content for edge-case topics not covered in the guide. How can they improve consistency?

A. Reduce the brand guide to key bullet points to avoid Claude getting confused by verbose instructions
B. Add few-shot examples showing correct brand voice application for various scenarios, including edge cases similar to the problematic ones
C. Use a PostToolUse classifier that checks every response against the brand guide and regenerates if off-brand
D. Fine-tune a custom model on brand-compliant responses 

  Show Answer

Question # 8

A developer is building a multi-step data pipeline with Claude. Step 1 extracts data from PDFs, Step 2normalizes the data, Step 3 performs analysis, and Step 4 generates a report. Each step's output feedsinto the next. After Step 2, the normalized data is 40K tokens. They worry Step 3 will lose accuracyover long context. What prompting pattern optimizes this pipeline?

A. Run all 4 steps in a single conversation to maintain context
B. Combine Steps 1-2 and 3-4 into two larger steps to reduce the number of calls 
C. Run all steps in parallel with separate conversations 
D. Use prompt chaining: run each step as a separate API call, passing only the necessary output from the previous step as input to the next 

  Show Answer

Question # 9

An engineering manager is building an enterprise agent platform that serves multiple departments.Each department has its own MCP servers, tools, and access controls. The IT department should accessinfrastructure tools, HR should access employee tools, and Finance should access accounting tools.How should tool access be scoped?

A. Give all departments access to all tools and rely on prompt instructions for scope 
B. Create separate Claude API keys per department with different tool permissions 
C. Use per-agent tool configurations that expose only department-appropriate tools, with MCP server permissions enforcing access control at the tool execution layer
D. Use a single MCP server that checks the caller's department before returning results 

  Show Answer

Question # 10

A developer wants to use Claude for generating regex patterns from natural language descriptions.They use the Messages API with a simple prompt. The generated regex often has edge cases that fail.What approach improves regex generation quality?

A. Use a larger model (Opus instead of Sonnet) for better pattern generation 
B. Ask Claude to generate multiple regex variants and pick the best one 
C. Use extended thinking to let Claude reason through edge cases 
D. Provide test strings (both matching and non-matching examples) in the prompt, then use a tool that tests the generated regex against all examples and returns failures for iteration

  Show Answer

Question # 11

A developer implements compaction for a long-running code review session. After compaction, Claudeloses track of files it already reviewed and re-reviews them. What technique preserves the reviewprogress through compaction?

A. Use custom compaction instructions: 'Always preserve the list of reviewed files and their review status'
B. Maintain a scratchpad file (e.g., REVIEW_PROGRESS.md) listing completed reviews, with Claude reading it after compaction to restore state
C. Increase the compaction summary length to capture all reviewed files 
D. Disable compaction and manage context manually 

  Show Answer

Question # 12

A startup is designing a customer service agent. They want the agent to detect when a customer isfrustrated based on conversation patterns (multiple repeated questions, escalating language, long waittimes). The detection should trigger a different handling workflow. Where should frustration detectionlogic be implemented?

A. In the system prompt: 'Detect frustration and adjust your approach' 
B. In a PostToolUse hook that monitors the conversation for frustration indicators 
C. As a separate sentiment analysis tool that the agent calls periodically 
D. In the orchestrator as a classifier that analyzes each customer message and adjusts the agent's system prompt or routing based on sentiment signals

  Show Answer

Question # 13

A team implements a structured output pipeline where Claude generates quiz questions. Each questionmust have exactly 4 options and one correct answer. They use json_schema strict mode. Occasionally,two options are semantically identical (e.g., 'Use a load balancer' and 'Implement load balancing'). Theschema can't prevent this. What additional quality measure is needed?

A. Add a schema constraint for unique options (uniqueItems in JSON Schema) 
B. Implement a semantic similarity check in the application layer that compares all option pairs and flags near-duplicates for regeneration
C. Use extended thinking to encourage Claude to verify distinctness before generating 
D. Add a system prompt instruction: 'All options must be semantically distinct' 

  Show Answer

Question # 14

Your organization is designing a prompt caching strategy. Their application has: (1) a 3K token systemprompt, (2) a 10K token knowledge base, (3) a 2K token conversation history, and (4) user messagesaveraging 200 tokens. They're using Claude Sonnet 4.5 which has a minimum 1024 token cachethreshold. Which portions should be cached?

A. System prompt (3K) + knowledge base (10K) as a single cached prefix, since both are stable and together form a 13K prefix well above the minimum threshold
B. Only the system prompt (3K) since it's stable across all requests 
C. Cache everything including conversation history 
D. Only the knowledge base since it's the largest component 

  Show Answer

Question # 15

A developer creates an MCP tool that wraps a SOAP-based legacy API. The SOAP API returns XMLwith deeply nested namespaced elements. What transformation should the MCP tool apply beforereturning results to Claude?

A. Return the raw XML — Claude can parse XML natively 
B. Base64-encode the XML and return it as a string 
C. Convert to a flat key-value pair format 
D. Convert to a simplified JSON structure that strips namespaces and flattens unnecessary nesting, keeping only the business-relevant fields

  Show Answer