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Analyze code structure, dependencies, and semantics with deterministic graph-native understanding.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "arbor" yet — see the docs or source repo.
Using the code graph, analyze the full call chain of the function processOrder. List which modules it calls, which entry points trigger it, and highlight key dependencies.
A clear call chain, upstream and downstream function list, and key module dependency notes.
Explain how the authentication flow is implemented in this project, including the core files, main classes, key functions, and their relationships, in order from request entry to permission validation.
A structured explanation of the authentication flow for quickly understanding the system design.
If I modify the user status field in UserService, analyze the potentially affected functions, APIs, tests, and downstream modules, and provide a list of risk points.
An impact analysis covering affected components, scope of change, and major regression risks.
Query, understand, and edit large multilingual codebases with AI knowledge graphs.
Turn codebases into knowledge graphs for architecture and dependency understanding.
Gives AI coding agents semantic code graphs for faster, more precise answers.
Index codebases into a knowledge graph for search, analysis, and code understanding.
Embed your codebase for fast semantic search with Graph RAG.
Query code structure precisely to understand and analyze large codebases faster.