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You are building developer-productivity tools using the Claude Agent SDK.

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, and Glob—and integrates with Model Context Protocol (MCP) servers.

During testing, you observe that in extended exploration sessions lasting more than 30 minutes, the agent starts giving inconsistent answers about code structure it discussed earlier. Engineers report having to repeat context about modules they have already explored.

What is the most effective approach to address this?

A.

Have the agent maintain a scratchpad file that records key findings and reference it during subsequent questions.

B.

Implement automatic context clearing every 15 minutes to ensure the agent starts with fresh, uncontaminated context.

C.

Switch to a higher-capacity model tier to provide more context-window space for accumulated exploration data.

D.

Create summaries of all source files before exploration begins, loading only those compressed representations into context.

Anthropic CCAR-F Summary

  • Vendor: Anthropic
  • Product: CCAR-F
  • Update on: Aug 26, 2026
  • Questions: 152
Price: $52.5  $149.99
Buy Now CCAR-F PDF + Testing Engine Pack

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