# Working with large codebases

Handling enterprise-scale repositories requires specific strategies and optimizations.

## Code Analysis Strategy

### **Intelligent Searching**

* Agents download code to remote servers
* Use reference-based searching for efficiency
* Progressive analysis from entry points

### **Token Optimization**

* Focus on relevant code sections
* Incremental context building
* Caching of analysis results

## Performance Considerations

```
Repository Size    Recommended Approach
──────────────    ───────────────────
< 100K LOC        Standard analysis
100K-1M LOC       Targeted search patterns
> 1M LOC          Modular execution strategy
```

## Large Codebase Best Practices

1. **Divide and Conquer**
   * Break transformations into smaller Runbooks
   * Focus on specific modules or packages
   * Use incremental rollout strategy
2. **Context Management**
   * Carefully curate relevant documentation
   * Use MCP for external context
   * Limit scope to necessary files
3. **Resource Planning**
   * Monitor token usage trends
   * Scale agent containers as needed
   * Use caching effectively


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.aviator.co/runbooks/concepts/working-with-large-codebases.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.