codewrench 0.1.0

A multi-language code performance analyser with static analysis and AI-powered fix generation.

🔧 wrench

Point it at your code. Get back what's slow and how to fix it.

Wrench is a multi-language performance analyser that combines static analysis with AI-powered explanations. It finds real performance issues in your code — nested loops, inefficient patterns, bad practices — then explains exactly why they're a problem and shows you the fix.

No cloud, no setup hell, no enterprise pricing. Just run it on a file.

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What it catches

High priority

• Nested loops (O(n²) and worse)
• Expensive function calls inside loops
• Repeated attribute access that should be cached
• String concatenation with + in loops

Medium priority

• List appends inside nested loops
• Unnecessary list(range(n)) creation
• Bare except: and overly broad except Exception
• Global variable access inside loops
• Mutable default arguments

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Supported languages

Language	Extension
Python	.py
JavaScript	.js
TypeScript	.ts
Go	.go
C	.c
C++	.cpp, .cc

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Installation

git clone https://github.com/yourusername/wrench.git
cd wrench
python -m venv venv
source venv/bin/activate        # Mac/Linux
venv\Scripts\activate           # Windows
pip install -r requirements.txt

Create a .env file in the project root:

GROQ_API_KEY=your_key_here

Get a free Groq API key at console.groq.com

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Usage

python main.py yourfile.py
python main.py app.js
python main.py main.go
python main.py server.cpp

That's it. Wrench detects the language from the file extension automatically.

Example output

Nested loop at line 19 — potential O(n²)
String concatenation at line 22 — use ''.join() instead
Function call 'expensive_function' inside loop at line 25 — consider moving it out
Bare except at line 40 — catches everything including system exceptions, be specific

--- AI Analysis ---

1. Nested loop at line 19
   Problem: Two nested loops over the same data gives you O(n²) time complexity.
   For 1000 items that's 1,000,000 iterations instead of 1,000.

   Fix:
   # before
   for i in items:
       for j in items:
           process(i, j)

   # after — use itertools or restructure with a dict lookup
   lookup = {item: process(item) for item in items}

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How it works

your file
    ↓
Tree-sitter parses it into a syntax tree
    ↓
IR translator converts to language-agnostic representation
    ↓
Detectors run static analysis on the IR
    ↓
Findings sent to Groq (Llama 3.3 70B)
    ↓
Plain English explanation + fix

The static analysis layer is deterministic — it either finds a nested loop or it doesn't. No hallucination. The AI layer explains what the detectors already confirmed exists.

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Roadmap

• Static analysis (Python, JS, TS, Go, C, C++)
• AI-powered explanations and fixes
• Multi-language IR architecture
• Runtime profiling (Layer 3)
• More detectors
• pip install wrench support
• Web UI

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Project structure

wrench/
├── detectors/
│   ├── base.py         ← depth tracking, core visitor
│   ├── high.py         ← high priority detectors
│   └── medium.py       ← medium priority detectors
├── languages/
│   ├── python_rules.py ← Tree-sitter node mappings per language
│   ├── js_rules.py
│   └── ...
├── ir.py               ← language-agnostic IR node
├── ir_translator.py    ← Tree-sitter → IR translation
├── parser_engine.py    ← language detection + parser setup
├── ai_engine.py        ← Groq integration
└── main.py             ← entry point

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Contributing

Pull requests welcome. If you want to add a new language, add a rules file in languages/ mapping Tree-sitter node types to the generic IR types. That's it — the detectors work on all languages automatically.

Open an issue first for anything major.

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Built by [@vishaddjain]