What languages does Smart Explore support?

It leverages tree-sitter for parsing, which supports most major programming languages including TypeScript, JavaScript, Python, Rust, Go, Java, and C++.

How does Smart Explore save tokens in Claude Code?

It uses AST parsing to provide structural maps of your code first, allowing the AI to 'unfold' only the specific functions or classes it needs to see rather than reading thousands of lines of irrelevant code.

What is the difference between smart_search and smart_outline?

smart_search performs a broad search for symbols across a directory based on a query, while smart_outline generates a complete structural skeleton (imports, classes, methods) for one specific file.

Does this skill replace the standard Grep and Read tools?

Yes, for code exploration it is designed to replace the standard Glob → Grep → Read cycle. However, standard tools are still recommended for non-code files like JSON, Markdown, or configuration files.

Smart Explore for Claude Code

Name: Smart Explore for Claude Code
Author: micsapp

bymicsapp

0•

Herramientas para Desarrolladores

Optimizes codebase exploration and navigation using AST-based structural parsing to drastically reduce token consumption.

Smart Explore is a high-efficiency navigation skill for Claude Code that replaces the standard Read, Grep, and Glob cycle with intelligent, tree-sitter-powered structural search. By indexing codebases first and fetching specific implementation details on demand, it allows developers to map out complex repositories without exhausting context windows or token limits. It provides a three-layered workflow—searching across directories, outlining specific file structures, and unfolding precise symbol implementations—resulting in up to an 18x reduction in token usage compared to traditional exploration agents.

Características Principales

01Significant token savings ranging from 4x to 18x compared to full-file reads.

02Comprehensive file outlining to view methods, imports, and properties without implementation noise.

03Precise symbol unfolding to retrieve specific source code nodes via tree-sitter boundaries.

040 GitHub stars

05AST-based structural search to locate functions and classes across directories.

06Automatic override of default discovery behaviors for more efficient agent performance.

Casos de Uso

01Navigating and understanding massive legacy codebases with deep directory structures.

02Performing rapid code audits and documentation tasks with minimal token overhead.

03Locating cross-cutting feature implementations without manual grepping or file scanning.

Características Principales

01Significant token savings ranging from 4x to 18x compared to full-file reads.

02Comprehensive file outlining to view methods, imports, and properties without implementation noise.

03Precise symbol unfolding to retrieve specific source code nodes via tree-sitter boundaries.

040 GitHub stars

05AST-based structural search to locate functions and classes across directories.

06Automatic override of default discovery behaviors for more efficient agent performance.

Casos de Uso

01Navigating and understanding massive legacy codebases with deep directory structures.

02Performing rapid code audits and documentation tasks with minimal token overhead.

03Locating cross-cutting feature implementations without manual grepping or file scanning.