Your order management system requires tools for three distinct operations: issuing refunds (requires amount and reason), canceling orders (requires reason), and requesting reshipments (requires shipping address). Each operation shares an order_id parameter but has different additional requirements. You notice during testing that with your current unified tool design, the agent frequently omits required parameters or includes irrelevant ones. What design change will most effectively improve parameter accuracy?

• A. Split into three separate tools (issue_refund, cancel_order, request_reshipment), each defining only the parameters required for that specific operation.
• B. Keep one unified tool with all parameters marked optional, but add detailed few-shot examples in the system prompt showing correct parameter combinations for each operation type.
• C. Keep one unified tool but add JSON Schema if-then-else conditionals to enforce that parameters like amount are required only when the operation type is "refund".
• D. Keep one unified tool with a nested operation_details object parameter whose internal structure varies by operation type, documented in the tool description.

The web search agent has gathered several relevant sources for a research topic. The document analysis agent now needs to examine these sources. How does information typically flow between these two specialized subagents?

• A. The coordinator agent receives the web search agent's output and includes relevant findings in the prompt when invoking the document analysis agent.
• B. The agents communicate through an event-driven message queue, with the document analysis agent subscribing to web search completion events.
• C. The web search agent directly invokes the document analysis agent, passing the discovered sources as parameters.
• D. Both agents access a shared memory store where the web search agent writes findings and the document analysis agent reads them.

Your process_refund tool returns two types of errors: technical errors ("503 Service Unavailable",
"Connection timeout") that are transient (5% of calls), and business errors ("Order exceeds
30 day return window", "Item already refunded") that are permanent (12% of calls). Monitoring shows the agent wastes 3-4 turns retrying business errors that can never succeed. Currently, both error types return only a plain text message to Claude. What's the most effective way to reduce wasted retries while improving customer-facing response quality?

• A. Implement automatic retry logic at the tool level for technical errors only, passing business errors to Claude without retries.
• B. Add few-shot examples showing how to distinguish retriable from non-retriable errors by parsing error message text.
• C. Add a check_refund_eligibility tool that must be called before process_refund to prevent business rule violations.
• D. Return structured error responses with retriable: false for business errors and a customer-friendly explanation for Claude to use.

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. Create a shared-stendards.md that uses @imports to combine all three standards, then have each package's CLAUDE.md import that combined file.
• B. 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."
• 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 .claude/rules/ files for each standard with YAML frontmatter paths listing every package directory where that standard should apply.

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 agent needs to insert a new helper function into the middle of a 150-line utility module, between two existing functions. The Edit tool fails because its old_string parameter cannot find unique text to match - the file has repetitive docstrings, variable names, and structural patterns.
What's the most reliable way to complete this insertion?

• A. Use Edit with an extremely long old_string capturing 30+ lines of context to guarantee uniqueness
• B. Use Bash to append the function definition to the end of the file using heredoc syntax
• C. Use Edit's replace_all parameter to target a common pattern and embed the new function in the replacement text
• D. Use Read to load the file, add the function at the appropriate location, then Write the updated file