CCA-F 무료 덤프문제 온라인 액세스

A customer raises three separate issues during one session: a refund inquiry (turns 1-15), a subscription question (turns 16-30), and a payment method update (turns 31-45). At turn 48, the customer asks "What happened with my refund?" The conversation is approaching context limits.
What strategy best maintains the agent's ability to address all issues throughout the session?

• A.Extract and persist structured issue data (order IDs, amounts, statuses) into a separate context layer.
• B.Summarize earlier turns into a narrative description, preserving full message history only for the active issue.
• C.Rely on MCP tools to re-fetch relevant information on demand when the customer references earlier issues.
• D.Implement sliding window context that retains the most recent 30 turns.

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 caching layer for API responses to speed up the /products endpoint. You have a rough idea-Redis with a 5-minute TTL-but you're new to production caching and aren't sure what other considerations a robust implementation requires. What's the most effective way to start your iterative workflow?

• A.Use plan mode to analyze the current/products endpoint implementation, then provide your caching requirements once Claude explains how the existing code is structured.
• B.Start with a minimal request: "Add Redis caching to /products with 5-minute TTL." Add features and fix issues through follow-up prompts as problems surface during testing.
• C.Write a specification with your known requirements and "TBD" markers for uncertain areas, having Claude propose solutions for each TBD as it implements.
• D.Ask Claude to interview you about the caching requirements before implementing, surfacing considerations like invalidation strategies, cache layers, consistency guarantees, and failure modes.

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.
Your code review assistant needs to analyze pull requests and provide feedback on three aspects: code style compliance, potential security issues, and documentation completeness.
Each aspect requires reading files, running analysis tools, and generating a report section. The review process follows the same three-step workflow for every PR. Which task decomposition pattern is most appropriate for this workflow?

• A.Orchestrator-workers - have a central LLM analyze each PR to dynamically determine which checks are needed, then delegate to specialized worker LLMs for each identified subtask.
• B.Routing - classify each PR by type (feature, bugfix, refactor) first, then route to different review prompts optimized for that category.
• C.Prompt chaining - break the review into sequential steps where each aspect (style, security, documentation) is analyzed separately, with outputs combined in a final synthesis step.
• D.Single comprehensive prompt - include all instructions in one prompt and let the model handle all three aspects simultaneously.

A financial services company plans to integrate Claude into an internal document analysis platform. The architects want to minimize exposure of confidential client information while maintaining high-quality responses. Which approach BEST aligns with Anthropic's recommended architecture?

• A.Remove unnecessary sensitive information before sending prompts whenever possible.
• B.Store every prompt permanently for auditing.
• C.Replace Claude with a smaller local model regardless of task complexity.
• D.Send every document without preprocessing to maximize context.

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 monorepo contains shared coding standards in /docs/standards/ : security-rules.md (for services handling user data), testing-petterns.md (for all packages), and api-conventions.md (for API-facing services). Your 15 packages are organized by feature domain ( /packages/auth/,
/packages/billing/, /packages/notifications/ , etc.) without naming conventions indicating which handle user data or expose APIs. Package maintainers are expected to configure their own local development settings, as they understand their package's domain requirements. Currently, all package CLAUDE.md files duplicate all three standards, applying irrelevant guidance. What's the most effective approach?

• A.Put all standards in the root CLAUDE.md with override instructions like "ignore security-rules.md when working in packages that don't handle user data."
• B.Create .claude/rules/ files for each standard with YAML frontmatter paths listing every package directory where that standard should apply.
• C.Use @imports in each package's CLAUDE.md to reference only the specific standard files relevant to that package, based on the maintainer's domain knowledge.
• D.Create a shared-stendards.md that uses @imports to combine all three standards, then have each package's CLAUDE.md import that combined file.