Methods for achieving consistency between AI-generated code and project technology stacks
Sidekick CLI can effectively solve this problem through the project guide file and model switching function, the specific solution is as follows:
- Creating the SIDEKICK.md guide file: Create this file in the project root directory, explicitly specifying the technology stack to be used (e.g., Python/Flask), the code style (e.g., PEP 8), and the project structure (e.g., MVC), and the AI will generate code based on these constraints
Sample Content:
“`
# Tech Stack: Python 3.10, Flask, PostgreSQL
# Coding Style: Google Python Style Guide
“` - Using the dedicated model switching function: Switch to the AI model best suited to the current tech stack via the `sidekick /model` command (e.g. Python projects can prioritize gpt-4)
- Real-time adjustments during the development phase: Quickly undo non-conforming results in conjunction with the `/undo` command and regenerate them by adding more detailed prompts.
This answer comes from the articleSidekick CLI: An Open Source Claude Code Replacement ToolThe
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