Graph‑Native Intelligence for Codebases
Know what breaks before you break it.
Arbor is a local‑first impact analysis engine for large codebases. Instead of treating code as text, Arbor parses your project into a semantic dependency graph. This lets you trace real execution paths—callers, callees, imports, inheritance, and cross‑file relationships—so you can confidently understand the consequences of change.
Unlike keyword search or vector‑based RAG systems, Arbor answers questions like:
“If I change this function, what actually breaks?”
with structural certainty, not probabilistic guesses.
Before refactoring detect_language, inspect its true impact:
$ arbor refactor detect_language
Analyzing detect_language...
Confidence: High | Role: Core Logic
• 15 callers, 3 dependencies
• Well-connected with manageable impact
> 18 nodes affected (4 direct, 14 transitive)
Immediate Impact:
• parse_file (function)
• get_parser (function)
Recommendation: Proceed with caution. Verify affected callers.This is execution‑aware analysis, not text matching.
Arbor v1.4 ships with a native GUI for interactive impact analysis.
arbor gui- Symbol Search – Instantly locate functions, classes, and methods
- Impact Visualization – Explore direct and transitive dependencies
- Privacy‑Safe – File paths are hidden by default for clean screenshots
- Export – Copy results as Markdown for PRs and design docs
The CLI and GUI share the same analysis engine—no feature gaps.
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Install Arbor (CLI + GUI):
cargo install arbor-graph-cli
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Run Impact Analysis:
cd your-project arbor refactor <symbol-name>
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Launch the GUI:
arbor gui
📘 See the Quickstart Guide for advanced workflows.
Most AI coding tools treat code as unstructured text, relying on vector similarity. This approach is fast—but imprecise.
Arbor builds a graph.
Every function, class, and module is a node. Every call, import, and reference is an edge. When you ask a question, Arbor follows the graph—the same way your program executes.
Traditional RAG: Arbor Graph Analysis:
"auth" → 47 results AuthController
(keyword similarity) ├── calls → TokenMiddleware
├── queries → UserRepository
└── emits → AuthEvent
The result: deterministic, explainable answers.
A lightweight, high‑performance interface bundled directly with Arbor—no browser, no server.
Each result includes an explainable confidence level:
- High – Fully resolved, statically verifiable paths
- Medium – Partial uncertainty (e.g., polymorphism)
- Low – Heuristic or dynamic resolution
Arbor infers architectural roles automatically:
- Entry Point – APIs, CLIs, main functions
- Core Logic – Domain and business rules
- Utility – Widely reused helpers
- Adapter – Interfaces, boundaries, and bridges
Arbor implements the Model Context Protocol (MCP), enabling LLMs (e.g., Claude) to query the graph directly:
find_path(start, end)– Trace logic flowanalyze_impact(node)– Compute blast radiusget_context(node)– Retrieve semantically related code
A global symbol table resolves:
- Imports and re‑exports
- Inheritance and interfaces
- Overloads and namespaces
User in auth.ts is never confused with User in types.ts.
| Language | Status | Parser Coverage |
|---|---|---|
| Rust | ✅ | Functions, Structs, Traits, Impls, Macros |
| TypeScript | ✅ | Classes, Interfaces, Types, Imports, JSX |
| JavaScript | ✅ | Functions, Classes, Vars, Imports |
| Python | ✅ | Classes, Functions, Imports, Decorators |
| Go | ✅ | Structs, Interfaces, Funcs, Methods |
| Java | ✅ | Classes, Interfaces, Methods, Fields |
| C | ✅ | Structs, Functions, Enums, Typedefs |
| C++ | ✅ | Classes, Namespaces, Templates |
| C# | ✅ | Classes, Methods, Properties, Interfaces |
| Dart | ✅ | Classes, Mixins, Widgets |
Python note: Decorators,
__init__.py, and@dataclassare statically analyzed. Dynamic dispatch is flagged with reduced confidence.
git clone https://github.com/Anandb71/arbor.git
cd arbor/crates
cargo build --releasesudo apt-get install -y pkg-config libx11-dev libxcb-shape0-dev libxcb-xfixes0-dev \
libxkbcommon-dev libgtk-3-dev libfontconfig1-dev libasound2-dev libssl-dev cmake- .gitignore – Arbor respects it (
arbor status --files) - File type – Ensure the extension is supported
- Empty files – Skipped (except
__init__.py) - Dynamic calls –
eval/ runtime reflection may not resolve - Case sensitivity – Use
arbor query <partial>to search
Run arbor status to verify file detection and parser health.
Arbor is Local‑First by design:
- No data exfiltration
- Fully offline
- No API keys
- Fully open source
Your code never leaves your machine.
MIT License. See LICENSE for details.