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

Your agent has spent 25 minutes exploring a game engine’s rendering subsystem—reading shader code, buffer management, and frame synchronization logic. An engineer now asks it to understand how the physics engine integrates with rendering for collision debug overlays. You notice recent responses reference “typical rendering patterns” rather than the specific VulkanPipeline and FrameGraph classes it discovered earlier.

What’s the most effective approach?

A.

Spawn a sub-agent to explore physics independently, then manually synthesize its findings with the rendering knowledge accumulated in the main conversation.

B.

Use /clear to reset context completely, then start fresh with physics exploration using file paths from the project’s CLAUDE.md.

C.

Summarize key rendering findings, then spawn a sub-agent for physics exploration with that summary in its initial context.

D.

Continue in the current context with more targeted prompts referencing the specific classes by name.

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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