The synthesis agent receives summarized findings from the web search and document analysis agents, then passes a consolidated summary to the report generator. During testing, you discover the generated reports make factual claims without proper citations - the report generator cannot attribute statements to their original sources because that metadata was lost during the summarization steps. What's the most effective approach to ensure proper source attribution in the final reports?

• A. Instruct the synthesis agent to embed source references inline within its summary text using a consistent citation format.
• B. Skip summarization and pass full raw outputs from web search and document analysis directly to the report generator.
• C. Have each agent output structured data separating content summaries from source metadata (URLs, document names, page numbers).
• D. Have the report generator query the web search agent to re-locate sources for claims in the final report.

After investigating a billing dispute over 25+ turns, you've identified that duplicate charges occurred due to a payment gateway timeout triggering retry logic. The required refund ($847) exceeds your $500 authorization limit You need to call escalate_to_human, and the human agent won't have access to your conversation transcript. What context should you pass to enable effective resolution?

• A. Your diagnosis and the refund amount only.
• B. The complete conversation transcript with all tool results.
• C. The customer's original complaint verbatim plus the tool result excerpts showing duplicate transactions.
• D. A structured summary: customer ID, root cause, refund amount, and recommended action.

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.
Your extraction pipeline processes restaurant menus and must output structured JSON with fields for item names, descriptions, prices, and dietary tags. Some menus use inconsistent formatting-- prices as "$12" vs "12.00", dietary info as icons vs text.
What's the most reliable approach?

• A. Use separate extraction calls for each field to ensure consistent handling of each type.
• B. Define a strict output schema and include format normalization rules in your prompt.
• C. Extract data as-is and normalize formats in post-processing code after Claude returns.
• D. Request multiple extraction attempts per document and select the most common format.

You are building a structured data extraction system using Claude. The system extracts information from unstructured documents, validates the output using JSON schemas, and maintains high accuracy. It must handle edge cases gracefully and integrate with downstream systems.
Your extraction system parses e-commerce product descriptions to extract specifications such as dimensions, weight, and materials into JSON. Despite having a well-defined schema, the model inconsistently extracts the materials field--sometimes returning "cotton blend," other times
"Cotton/Polyester mix," and occasionally omitting the field when material information is clearly present in the source.
What is the most effective way to improve extraction consistency?

• A. Set the temperature to 0 to eliminate randomness and ensure deterministic outputs.
• B. Make the materials field required instead of optional in the schema to force the model to always extract a value.
• C. Add few-shot examples showing two or three complete input-output pairs with standardized material-description formats.
• D. Switch to a more capable model tier because inconsistent extraction indicates insufficient model capability.

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. As a detailed instruction block in the project's root CLAUDE.md file
• B. In .claude/skills/migrate-component/SKILL.md at the project root, committed to version control
• C. In ~/.claude/skills/migrate-component/SKILL.md on each developer's machine
• D. In the project's.claude/settings.json using a skillOverrides entry to register and define the workflow