You are building developer productivity tools using the Claude Agent SDK. The agent helps engineers explore…

Question

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 asks the agent to understand how the caching layer works before adding a new cache invalidation trigger. After initial Grep searches, the agent has identified that caching logic spans 15 files including decorators, middleware, and service classes (~8,000 lines total). What’s the most effective next step for building understanding while managing context constraints?

Accepted Answer

C. Analyze imports and class hierarchies to identify the base cache class, Read that file to understand the interface, then trace specific invalidation implementations.

Answer

A. Use the Read tool to sequentially load all 15 files, building complete understanding across the full caching implementation.

Answer

B. Use Glob to find files matching common caching patterns (cache.py, caching/), prioritize the largest files by reading them first, then check smaller files for gaps.

Answer

D. Use Grep to search for “invalidate” and “expire” patterns across all files, then Read only those specific line ranges with minimal surrounding context.

Question 68