[Help] Optimizing Claude Code for Large Codebases like Velox to Improve Efficiency and Reduce Token Usage

Description

Most of the time, we work with large codebases featuring multiple components, modules, and code files—such as the Velox project (facebookincubator/velox). Velox is a massive C++ execution engine library with a complex structure (e.g., numerous subdirectories, interdependent modules, and extensive logic). While Claude Code is incredibly powerful for understanding codebases and assisting with tasks, I’m concerned about its efficiency and token consumption when applied to such large-scale projects.

Right now, I’m working on Velox, and I’m hesitant to run Claude Code extensively because it might consume all my API tokens quickly, especially given the size of the codebase. Without clear guidance, it’s hard to know how to use Claude Code in a way that maximizes accuracy and minimizes waste.

Request

Could you help us understand how to use Claude Code more efficiently in scenarios like this? Specifically:

1. Token Optimization: How can we reduce token usage when working with large codebases? Are there strategies to limit context size (e.g., feeding only relevant files or summaries) without losing accuracy?
2. Accuracy Improvement: What’s the best way to structure prompts or workflows to ensure Claude Code understands complex, multi-module projects like Velox?
3. Documentation: Do you have a detailed guide or examples showing how to optimize Claude Code for massive codebases? If not, could you provide some practical tips or add this to your documentation?
4. Velox-Specific Tips (Optional): Since I’m working on Velox, any tailored advice for navigating its structure (e.g., focusing on key directories like velox/core or velox/functions) would be a bonus!

Current Challenges

• Running Claude Code on the full Velox repo feels impractical due to token limits.
• I’m unsure how to break down the codebase into manageable chunks for Claude to process effectively.
• Lack of clarity on whether Claude Code can prioritize critical files or components over less relevant ones.

Why This Matters

For developers working on enterprise-scale projects like Velox, efficient use of Claude Code could save significant time and cost. Clear guidance would make it a go-to tool without the fear of burning through tokens or getting suboptimal results.

Additional Info

• Project: facebookincubator/velox
• Claude Code Version: [latest beta as of March 2025]
• Environment: Terminal-based usage, standard setup per Anthropic docs.

Some Ideas which I am following :-

• Summarize First: Before running Claude Code, manually create a ~5K token markdown spec of Velox’s key components (e.g., core, functions, exec). Feed this as context instead of the whole repo. Example prompt: “Here’s a spec of Velox: [paste spec]. How does the exec module work?”
• Chunking: Focus on one directory at a time (e.g., velox/core). Use: claude "explain the QueryContext class in velox/core/query.h".
• Low Temperature: For precision on Velox’s technical details, add “Use low temperature (0.5)” to your prompts to keep responses strict and code-focused.

Thanks for any help or pointers you can provide! I’d love to make the most of Claude Code without breaking the bank or losing accuracy.