Grit is an AI agent tool for source code search and modification, whose core is GritQL—a declarative query language. The design goal of GritQL is to enable developers to find and modify code patterns in large codebases in a simple and extensible way.
In terms of use, Grit is mainly used for scenarios such as automating large-scale code migrations, custom lint rules, code quality improvements, and dependency upgrades. For example, it can migrate APIs, frameworks, or refactor codebases across millions of lines of code, and can also enforce team-specific code standards.
Main capabilities include:
- Simple and easy to use: any code snippet is a valid GritQL query, with no need to learn AST details.
- High performance: uses Rust and query optimization, and can scale to codebases of more than 10 million lines.
- Modular: built-in module system, with access to more than 200 standard patterns, and also supports sharing custom patterns.
- Multi-language support: can rewrite JavaScript/TypeScript, Python, JSON, Java, Terraform, Solidity, CSS, Markdown, YAML, Rust, Go, or SQL.
- Automatic fixes: GritQL makes it easy to include automatic fix rules, speeding up fixes.
- Pattern search: search for patterns using backticks and metavariables (such as $msg).
- Custom lint: patterns can be saved as custom lints, and specific cases can be excluded through powerful where clauses.
In terms of usage, users can learn GritQL step by step through an interactive tutorial, consult the complete language reference documentation, and install and use the Grit CLI. Official resources provide a getting started guide, language reference, and CLI installation and usage instructions.
Applicable scenarios include: large-scale migrations (APIs, frameworks, codebase refactoring), custom lint (team code standards and best practices), code quality improvements (systematically improving code quality with consistent patterns), and dependency upgrades (handling breaking changes).
In terms of limitations, the official materials do not explicitly mention specific limitations, but as a query language tool, its effectiveness may depend on the accuracy of pattern writing and the structure of the target codebase.
