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1. 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 frequently migrates React components to Vue. You've written a step-by-step workflow for Claude Code to follow during each migration, and you want every developer on the team to invoke it by typing
/migrate-component . The workflow should stay in sync as the team iterates on it.
Where should you place the skill file?
A) In ~/.claude/skills/migrate-component/SKILL.md on each developer's machine.
B) In .claude/skills/migrate-component/SKILL.md at the project root, committed to version control.
C) As a detailed instruction block in the project's root CLAUDE.md file.
D) In the project's .claude/settings.json using a skillOverrides entry to register and define the workflow.
2. 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) 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.
B) 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.
C) 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.
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.
3. 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.
A customer returns 4 hours after their 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) 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.
B) 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.
C) Resume with full history and configure the agent to automatically re-call all previously used tools at session start to ensure data freshness.
D) 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.
4. 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 wants Claude to follow a detailed code review checklist (8 items covering API changes, test coverage, documentation, security, etc.) when reviewing pull requests. The team also uses Claude extensively for other tasks: writing new features, debugging production issues, and generating documentation. Currently, developers paste the checklist at the start of each review session.
Which approach best addresses this workflow need?
A) Create a /review slash command containing the checklist, invoked when starting reviews.
B) Add the checklist to the project's CLAUDE.md file under a "Code Review" section.
C) Create a dedicated review subagent with the checklist embedded in its configuration.
D) Configure plan mode as the default for code review sessions.
5. You are building a structured data extraction system using Claude. The system extracts information from unstructured documents, validates the output using JavaScript Object Notation (JSON) schemas, and maintains high accuracy. It must handle edge cases gracefully and integrate with downstream systems.
Testing reveals that when source documents are missing certain specifications, the model fabricates plausible- sounding values to satisfy your schema's required fields. For example, a document mentioning only dimensions receives a fabricated "weight: 2.3 kg" in the extraction output.
What schema design change most effectively addresses this hallucination behavior?
A) Change fields that may not exist in source documents from required to optional, allowing the model to omit them.
B) Implement semantic validation that verifies each extracted value appears in or can be inferred from the source document text.
C) Add explicit instructions to the prompt stating "only extract information explicitly stated in the document; use placeholder text for missing values."
D) Add a "confidence" field alongside each specification where the model self-reports its certainty, then filter out low-confidence extractions.
Solutions:
| Question # 1 Answer: B | Question # 2 Answer: B | Question # 3 Answer: A | Question # 4 Answer: A | Question # 5 Answer: A |
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