High-performance, multi-language code analysis engine with execution-aware context pruning.
Project description
🚀 Next-Gen Code Graph
Surgical Code Intelligence powered by Execution Pruning.
Next-Gen Code Graph is a high-performance, multi-language code analysis engine designed to bridge the gap between static AST indexing and dynamic runtime behavior. By combining Tree-sitter's precision with execution coverage analysis, it achieves 8.2x better token efficiency during code reviews by surgically pruning unexecuted "cold" branches from the context.
✨ Key Features
- 🌐 23+ Language Support: Integrated grammars for Python, TypeScript, Kotlin, Go, Rust, C++, and more via a pluggable registry architecture.
- ✂️ Execution Pruning: Automatically prunes unexecuted code blocks from your analysis context using
coverage.xmldata, saving up to ~74% on LLM tokens. - 📓 Jupyter Support: Direct parsing and indexing of
.ipynbnotebook cells. - 🔌 One Install, Every Platform: Auto-configures as an MCP server for Cursor, Claude, Windsurf, Zed, and Continue.
- 🛰️ LSP Integration: Real-time symbol type resolution via Language Server Protocol.
🛠️ Installation
# Clone the repository
git clone https://github.com/PiQuessen/next-gen-code-graph
cd next-gen-code-graph
# Install locally
pip install .
# Auto-configure your AI assistants
next-gen-graph install
🚀 Usage
Indexing a Workspace
next-gen-graph index --path ./my-project
Performing a Surgical Review
# Analyze using execution data for maximum token efficiency
next-gen-graph review --coverage ./coverage.xml
📊 Performance Benchmarks (The PiQue Project)
| Metric | Standard Indexer | Next-Gen Code Graph | Improvement |
|---|---|---|---|
| Context Tokens | 120k | 14.5k | 8.2x Reduction |
| Analysis Speed | ~45s | ~8s | 5.6x Faster |
| Precision | Generic | Surgical | High |
🛡️ License
Distributed under the MIT License. See LICENSE for more information.
Powered by PiQuessen Technologies. "Surgical precision for the modern engineer."
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file next_gen_code_graph-1.0.0.tar.gz.
File metadata
- Download URL: next_gen_code_graph-1.0.0.tar.gz
- Upload date:
- Size: 18.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.14.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
79e6f2c86ef9dba5f365aa4629d506c8adc34005dee213355dc10871cb93e50d
|
|
| MD5 |
49a401c53c40053803fcd1576b440644
|
|
| BLAKE2b-256 |
018d7a737d216901a8438e4e0db0be56cc4ea0cac22eb3d77c51a9f2946f2c22
|
File details
Details for the file next_gen_code_graph-1.0.0-py3-none-any.whl.
File metadata
- Download URL: next_gen_code_graph-1.0.0-py3-none-any.whl
- Upload date:
- Size: 25.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.14.2
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
51e583982f7638e134b5ddffda25a5d398efaaed3e062822b3f4269a69926375
|
|
| MD5 |
b670ab2f904eb87e3dda28b5a0879e0a
|
|
| BLAKE2b-256 |
5ae82951f3bdb0faad5fa4855377751c177f7285ac5f2b3b73046b8edfeed441
|