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.
A critical bug is affecting production users. Error logs show exceptions in the OrderProcessing module with a clear stack trace pointing to a specific function. You haven't worked with this module before. What's the most effective approach?

• A. Use direct execution to examine the stack trace, read the relevant code, and implement a fix once you identify the root cause.
• B. Start with direct execution to gather initial information, then switch to plan mode to design a comprehensive solution before implementing any changes.
• C. Enter plan mode to explore the module's architecture and dependencies before attempting any fixes.
• D. Use plan mode to analyze the error in context of the module's design, enumerate potential root causes, and prioritize fixes systematically.

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 submits two requests:
- Request A: "Rename the getUserData function to fetchUserProfile
everywhere it's used."
- Request B: "Improve error handling throughout the data processing
module - add try/catch blocks, meaningful error messages, and ensure
failures don't silently corrupt data."
For which request does specifying an explicit multi-phase workflow (such as analyze -> propose
-> implement with review) most improve outcome quality?

• A. Request B, the error handling task
• B. Neither request benefits significantly
• C. Both requests benefit equally
• D. Request A, the function rename task

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.
During testing, you observe that in extended exploration sessions (30+ minutes), the agent starts giving inconsistent answers about code structure it discussed earlier. Engineers report having to repeat context about modules they've already explored. What's the most effective approach to address this?

• A. Have the agent maintain a scratchpad file that records key findings, referencing it for subsequent questions.
• B. Create summaries of all source files before exploration begins, loading only these compressed representations into context.
• C. Switch to a higher-capacity model tier to provide more context window space for accumulated exploration data.
• D. Implement automatic context clearing every 15 minutes to ensure the agent starts with fresh, uncontaminated context.

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

Which practice MOST improves prompt maintainability?

• A. Clearly separated sections with headings.
• B. One paragraph containing all instructions.
• C. Minimal punctuation.
• D. Random ordering.