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| Section | Weight | Objectives |
|---|---|---|
| Prompt Engineering & Structured Output | 20% | - Prompt design strategies - Improving Claude response quality and consistency - Structured output generation and validation |
| Agentic Architecture & Orchestration | 27% | - Designing agentic systems and workflows - Agent coordination and orchestration patterns - Selecting appropriate Claude architectures |
| Claude Code Configuration & Workflows | 20% | - Developer productivity workflows - Claude Code usage and configuration - Integrating Claude Code into development processes |
| Tool Design & MCP Integration | 18% | - Model Context Protocol (MCP) concepts and integration - Tool safety, reliability, and usability - Designing effective tools for Claude applications |
| Context Management & Reliability | 15% | - Production deployment considerations - Managing context windows and information flow - Evaluation and reliability strategies |
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NEW QUESTION # 177
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's exploration subagent spent 30 minutes analyzing a legacy payment system, reading 47 files and documenting data flows. The session was interrupted when the engineer's connection dropped. While away, a teammate merged a PR that renamed two utility functions.
The engineer wants to continue the same exploration.
What's the most effective approach?
Answer: D
Explanation:
Resuming the existing subagent preserves the expensive investigative context: files already inspected, data-flow relationships, hypotheses, and intermediate conclusions. Anthropic documents that session history contains prompts, tool calls, tool results, and responses, allowing an interrupted investigation to continue with its prior analysis intact. Subagent transcripts also persist within their parent session and can be resumed after an interruption or restart.
The engineer must nevertheless disclose the renamed utility functions. Anthropic explicitly distinguishes conversation persistence from filesystem persistence: resuming restores what the agent previously knew, but it does not freeze or snapshot the repository. Without the update, the subagent may search for obsolete symbols, misinterpret broken references, or rely on stale file paths.
NEW QUESTION # 178
You are integrating Claude Code into your Continuous Integration/Continuous Deployment (CI/CD) pipeline. The system runs automated code reviews, generates test cases, and provides feedback on pull requests. You need to design prompts that provide actionable feedback and minimize false positives.
Your pipeline runs:
PROMPT='You are a code reviewer. Analyze the provided diff for bugs,
security issues, and style violations.'
claude -p \
--dangerously-skip-permissions \
--system-prompt "$PROMPT" \
< diff.txt
The reviews complete and return feedback, but Claude only comments on the piped diff text--it never reads surrounding files in the checked-out repository to understand broader context, even when the diff modifies a function called by many other modules.
Which change to the invocation will cause Claude to inspect related repository files while still applying your custom review instructions?
Answer: B
Explanation:
Option D preserves Claude Code's standard coding-agent instructions while adding the specialized review criteria. Anthropic documents that --system-prompt replaces the entire default system prompt, including its tool guidance, safety instructions, and coding conventions. It does not technically disable tools, but removing that guidance can make the invocation behave like a narrowly scoped text processor. --append-system-prompt retains the default behavior and layers the review instructions on top.
The prompt should explicitly direct Claude to use Read, Glob, and Grep to inspect definitions, callers, tests, and related modules whenever the diff alone is insufficient.
NEW QUESTION # 179
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've asked Claude Code to build a PDF report generation feature. The initial implementation queries the database correctly, but the output has formatting issues: table columns are too narrow causing content truncation, dates display without proper formatting, and page break handling is incorrect. You've noticed these issues interact-changing column widths affects how dates render, and page breaks depend on content height.
What's the most effective approach for iterating toward a working solution?
Answer: C
Explanation:
The defects are coupled, so changing all three simultaneously would make it difficult to determine which modification caused an improvement or regression. Option C establishes a controlled sequence: correct the foundational column geometry, verify the resulting layout, format dates within the stabilized columns, and finally tune page breaks using the resulting content heights.
Anthropic recommends tight feedback loops and early course correction. It also advises supplying Claude with an executable or observable verification mechanism, such as a test, build result, generated fixture, or screenshot comparison. Claude can then make a focused change, inspect the output, and iterate until that specific condition is satisfied. ( https://code.claude.com/docs/en/best-practices ) Option A discards useful context from the functioning database implementation. Option B changes multiple interacting variables in one pass, making failures harder to isolate. Option D provides a useful visual target but does not replace precise technical constraints or incremental verification.
Each stage should have explicit acceptance criteria-for example, minimum column widths, expected date strings, and page-break fixtures using short and long content. Once a stage passes, its test becomes a regression guard for subsequent changes.
Official references/topics: Incremental Refinement; Tight Feedback Loops; Observable Verification; Regression Control.
NEW QUESTION # 180
You are building a customer support resolution agent using the Claude Agent SDK. The agent handles high- ambiguity requests like returns, billing disputes, and account issues. It has access to your backend systems through custom Model Context Protocol (MCP) tools ( get_customer , lookup_order , process_refund , escalate_to_human ). Your target is 80%+ first-contact resolution while knowing when to escalate.
Compliance requires that refunds exceeding $500 must automatically escalate to a human agent-this rule cannot be left to model discretion. Despite clear system prompt instructions, production logs show the agent occasionally processes high-value refunds directly (3% failure rate).
How should you achieve guaranteed compliance?
Answer: C
Explanation:
A mandatory compliance threshold must be enforced outside probabilistic model reasoning. A PreToolUse hook can inspect every attempted process_refund call before execution, compare its amount with the $500 threshold, and deny the call when the limit is exceeded. The host application can then create the human- escalation case using the validated customer and order context.
Anthropic describes hooks as deterministic controls that ensure required actions occur instead of relying on the model to choose them. Agent SDK documentation confirms that a single denying PreToolUse hook blocks the tool call, including MCP tools matched through their qualified tool names. ( https://docs.anthropic.com/en
/docs/claude-code/hooks-guide )
Options A and B improve expected behavior but cannot guarantee compliance. The stated production failure rate demonstrates that prompting alone is insufficient. Option C prevents the refund from completing, but the subsequent escalation still depends on Claude correctly interpreting the returned error and invoking the human tool. It therefore enforces the financial block but not the complete escalation requirement.
Option D enforces both sides of the policy at the orchestration boundary: deny the unauthorized action and route the case to an approved human process. The escalation action should be idempotent and auditable.
Official references/topics: PreToolUse hooks, deterministic policy enforcement, MCP tool interception, human-approval controls.
NEW QUESTION # 181
Your test-generation process produces unit tests for new code, but reviews show that 55% are low-value: trivial assertions that verify only that functions do not throw exceptions, tests that duplicate existing coverage, or tests that ignore your team's fixture conventions. How should you reduce the rate of low-value tests being generated in the first place?
Answer: B
Explanation:
The failures reflect missing project-specific knowledge: Claude does not know which fixtures are preferred, what the existing suite already covers, or what the team considers meaningful behaviour. Option C provides this information as persistent project context before test generation begins. This changes generation quality at the source instead of filtering weak tests after spending tokens to produce them.
Anthropic's CLAUDE.md documentation recommends storing shared build and test commands, coding standards, architectural decisions, conventions, and common workflows in a project CLAUDE.md. Testing guidance can define required behavioural assertions, fixture selection rules, duplication checks, naming conventions, and representative examples of acceptable and unacceptable tests.
NEW QUESTION # 182
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