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

A developer wants Claude to explain every reasoning step internally before answering. Why might this request be inappropriate?

• A. Temperature prevents explanations.
• B. Internal reasoning should not be relied upon as an application feature.
• C. Claude requires GPU acceleration.
• D. JSON cannot contain reasoning.

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.
A developer asks the agent to investigate why a specific API endpoint intermittently returns 500 errors. The codebase has 200+ files and the developer doesn't know which components are involved. The agent must trace the error through routing, middleware, business logic, and database layers. What task decomposition approach would be most effective?

• A. Have the agent first create a comprehensive plan mapping all code paths through the endpoint before beginning any file exploration or code reading.
• B. Run parallel worker agents that simultaneously investigate all four layers, then synthesize their findings to identify where the error originates.
• C. Define a fixed sequence of investigation steps upfront - grep for error patterns, then read error handlers, then check database queries, then examine middleware - executing each step regardless of intermediate findings.
• D. Have the agent dynamically generate investigation subtasks based on what it discovers at each step, adapting its exploration plan as new information about the error path emerges.

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 codebase exploration tool stores session IDs to allow engineers to continue investigations across work sessions. An engineer spent an hour yesterday analyzing a legacy authentication module, building context about its architecture and dependencies. They want to continue today.
The session ID is valid, but version control shows 3 of the 12 files the agent previously read were modified overnight by a teammate's merge. What approach best balances efficiency and accuracy?

• A. Resume the session without informing the agent about the changed files
• B. Resume the session and immediately have the agent re-read all 12 previously analyzed files
• C. Start fresh session to ensure the agent works with current codebase state without stale assumptions
• D. Resume the session and inform the agent which specific files changed for targeted re-analysis

After integrating a local MCP server providing code analysis tools (analyze_dependencies, find_dead_code, calculate _complexity), you verify the server is healthy and tools appear in the tools/list response. However, you observe that the agent consistently uses Grep to search for import statements instead of calling analyze_dependencies -even when users explicitly ask about "code dependencies." Examining tool definitions reveals:
MCP: analyze_ dependencies - "Analyzes dependency graph"
Built-in: Grep - "Search file contents for a pattern using regular
expressions. Returns matching lines with line numbers and surrounding
context."
What's the most effective approach to improve the agent's selection of MCP tools?

• A. Add routing instructions to the system prompt specifying that dependency-related questions should use MCP tools rather than Grep.
• B. Remove Grep from available tools when the MCP server is connected to eliminate functional overlap.
• C. Split analyze_dependencies into granular tools ( list_imports, resolve_transitive_deps, detect_circular_deps) so each has a focused purpose less likely to overlap with Grep.
• D. Expand MCP tool descriptions to detail capabilities and outputs - e.g., "Builds dependency graph showing direct imports, transitive dependencies, and cycles."