最新のCCA-F問題集で試験を準備する

Your MCP server includes archive_file(file_id) and delete_file(file_id) tools. Production logs show the agent calls delete_file when users ask to "remove old backups," but company policy requires archiving backup files. Both tools currently have minimal descriptions: "Archives a file" and
"Deletes a file." Which change most directly improves tool selection for this scenario?

• A. Implement server-side validation that rejects delete_file calls for files tagged as backups, returning an error message suggesting archive_file.
• B. Add a confirmation step that requires users to type "CONFIRM DELETE" before delete_file executes.
• C. Expand tool descriptions to clarify use cases, adding guidance like "Do not use for backup files" to delete_file.
• D. Add few-shot examples to the system prompt demonstrating that requests involving "backup" or
  "old" should use archive_file.

After 30+ turns, your conversational assistant shows noticeably slower responses and occasionally produces less coherent outputs. Investigation reveals: (1) average conversations reach 50,000 tokens by turn 35, (2) production logs show 94% of user messages only reference the previous 3-5 exchanges, (3) the 6% of queries referencing earlier context typically ask about information the user could easily re-state. Your goal is to improve response speed and quality while maintaining good user experience. What's the most effective approach?

• A. Build a retrieval system that stores all conversation turns and uses semantic search to pull in relevant historical context only when the current query appears to reference past information.
• B. Implement a summarization layer that progressively compresses older conversation turns into a running summary while keeping the most recent 5-6 turns verbatim, maintaining full historical context in condensed form.
• C. Implement a sliding window keeping only the system prompt and last 8-10 turns. When users reference earlier context, acknowledge the limitation and ask them to re-state the relevant information.
• D. Enable prompt caching and continue sending the complete conversation history, using cached prefixes to reduce per-request costs while preserving all context.

An enterprise wants Claude responses to remain professional across every interaction. Where should tone instructions primarily reside?

• A. API key description
• B. Retrieved documents
• C. User prompt only
• D. System prompt

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 asks the agent to understand how the caching layer works before adding a new cache invalidation trigger. After initial Grep searches, the agent has identified that caching logic spans 15 files including decorators, middleware, and service classes (~8,000 lines total). What's the most effective next step for building understanding while managing context constraints?

• A. Use the Read tool to sequentially load all 15 files, building complete understanding across the full caching implementation.
• B. Use Glob to find files matching common caching patterns (cache.py, caching/), prioritize the largest files by reading them first, then check smaller files for gaps.
• C. Use Grep to search for "invalidate" and "expire" patterns across all files, then Read only those specific line ranges with minimal surrounding context.
• D. Analyze imports and class hierarchies to identify the base cache class, Read that file to understand the interface, then trace specific invalidation implementations.

A customer sends: "This is frustrating. I've explained my issue twice and nothing is being resolved. I want to talk to a real person NOW." The agent has not yet called any tools to investigate their account. What should the agent do?

• A. Immediately call escalate_to_human with the conversation history.
• B. First call get_customer and lookup_order to gather account context, then escalate to a human agent.
• C. Briefly explain what the agent can help with and offer to resolve the issue quickly, escalating only if the customer repeats their request.
• D. Acknowledge the frustration and ask one targeted question to understand the specific issue before escalating.