ChocoVine enforces a Research → Test → Code loop for Claude Code, reducing hallucinations. It benefits engineering teams by ensuring AI-generated code is reliable. It integrates with Python workflows and connects to Claude Code.
git clone https://github.com/vneseyoungster/ChocoVine.gitChocoVine is a workflow wrapper for Claude Code that implements a strict Research → Plan → Build → Review loop to prevent hallucinations and unreliable code generation. It forces AI to write failing tests first, scan your entire codebase through sub-agents, and obtain your approval before implementing any changes. The tool scales to mid-to-large codebases by optimizing context usage, and includes commands for systematic research, architecture planning, test-driven implementation, and code review. Engineering teams benefit from reproducible AI-assisted development where you maintain architectural control and code quality is verified at each phase.
Install via `npx github:vneseyoungster/ChocoVine init` in your project directory. Configure your stack details in the generated `CLAUDE.md` file. Run `/cv:init` to scan your codebase, then use `/cv:research`, `/cv:plan`, `/cv:build`, and `/cv:review` commands to work through tasks with approval gates at each stage.
Building features with Google OAuth or complex authentication flows
Adding components to mid-to-large React or Next.js applications
Implementing features from Figma designs with automatic token and CSS extraction
Refactoring legacy code with systematic dead code cleanup and renaming
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/vneseyoungster/ChocoVineCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
I'm working on a Python project for [COMPANY] in the [INDUSTRY] sector. I need to implement a [FEATURE] using ChocoVine to ensure reliable code. Here's the [DATA] I have: [INSERT DATA]. Please follow the Research → Test → Code loop and provide the final code.
# Research Phase
Based on the provided data, I've identified the following key requirements for the inventory management system:
- Real-time stock level tracking
- Low stock alerts
- Integration with existing POS system
# Test Phase
I've created the following test cases to validate the implementation:
1. Test stock level updates
2. Test low stock alert triggers
3. Test POS system integration
# Code Phase
Here's the final implementation that passes all tests:
```python
class InventoryManager:
def __init__(self, pos_system):
self.stock = {}
self.pos_system = pos_system
self.low_stock_threshold = 10
def update_stock(self, item_id, quantity):
self.stock[item_id] = quantity
if quantity <= self.low_stock_threshold:
self._send_low_stock_alert(item_id)
def _send_low_stock_alert(self, item_id):
# Implementation of low stock alert
pass
def sync_with_pos(self):
# Implementation of POS system sync
pass
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