LintConfig

# LintConfig

An AI skill that automatically interprets coding standards, configures static analysis and linting tools, executes lint checks, and assists with code quality improvement. The skill supports both configuration-only workflows (e.g., "generate a linter config for a coding standard") and end-to-end quality enforcement workflows (e.g., "check this code against our coding standard and suggest fixes").

## Features

- **Automatic Coding Standard Parsing**: Converts natural language coding standards into formalized coding rules using a structured grammar. 
- **Intelligent Linter Configuration**: Automatically maps coding rules to appropriate linter rules and generates validated configuration files.
- **Multi-Linter Support**: Currently supports Checkstyle (Java) with extensible architecture for additional linters.
- **Coverage Analysis**: Classifies configuration coverage (Exact Match, Over-Approximation, Under-Approximation) to help you understand how well the linter configuration aligns with your coding standards.
- **End-to-End Workflow**: From coding standard → rules → configuration → linting → violation repair suggestions.
- **Rule Knowledge Base**: Pre-built index and complete information for Linter Rules.

## Why develop the tool: Mitigating AI Configuration Hallucinations

AI-assisted configuration tools, while powerful, can sometimes misinterpret coding standards and generate **incorrect** or **incomplete** configurations.  

**LintConfig** mitigates this by:

1. **Compiling coding standards into structured, standardized coding rules**.  
2. **Checking linter documentation to ensure valid configurations**.

<img src="fig/example3.png" width="60%" />

## Installation

### Prerequisites

- Python 3.x (for rule data preparation scripts, if needed)
- Access to one of the supported AI coding assistants
- Install **ripgrep** to enable search tool in Claude Code.  See [this issue](https://github.com/anthropics/claude-code/issues/6726) for details.

### Recom