Arbor FAQs

Question 1

What is Arbor and how does it benefit developers?

Accepted Answer

Arbor is a developer tool that indexes and compresses entire codebases into a structured symbol graph. It enables efficient, LLM-powered code navigation, allowing AI models to 'see' and understand complex projects by fitting vast amounts of code into their context windows.

Question 2

How does Arbor address LLM context window limitations?

Accepted Answer

Arbor's core feature is its ability to compress large codebases significantly, for example, reducing 1 million lines of code to approximately 500 lines. This optimization ensures LLMs can process and understand entire projects without hitting context window limits, providing highly relevant insights.

Question 3

What programming languages and formats does Arbor support?

Accepted Answer

Arbor supports indexing across 9 major programming languages, including Rust, Python, TypeScript, Go, C, C++, C#, and JavaScript. Additionally, it can index several non-code formats like Ansible, Terraform, SQL, Protobuf, OpenAPI, and Markdown.

Question 4

What are MCP tools in Arbor?

Accepted Answer

Arbor utilizes the Model Context Protocol (MCP) to offer 9 specialized tools like 'boot' (architecture overview), 'compact' (token-optimized skeleton), 'search' (fuzzy symbol search), and 'references' (all symbol references). These tools allow LLMs to surgically navigate and query the codebase at various granularities.

Question 5

Is Arbor efficient for large and frequently updated projects?

Accepted Answer

Yes, Arbor is built for performance. It can index large projects (e.g., 1.1M LOC in ~9.5 seconds) and provides rapid incremental re-indexing, typically completing updates in under 100 milliseconds, ensuring high performance for dynamic development environments.

Arbor

Arbor

주요 기능

사용 사례

주요 기능

사용 사례