tree-sitter
AST-based code analysis using tree-sitter. Use for parsing code structure, extracting symbols, finding patterns with tree-sitter queries, analyzing complexity, and understanding code architecture. Supports Python, JavaScript, TypeScript, Go, Rust, C, C++, Swift, Java, Kotlin, Julia, and more.
Best use case
tree-sitter is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
AST-based code analysis using tree-sitter. Use for parsing code structure, extracting symbols, finding patterns with tree-sitter queries, analyzing complexity, and understanding code architecture. Supports Python, JavaScript, TypeScript, Go, Rust, C, C++, Swift, Java, Kotlin, Julia, and more.
Teams using tree-sitter should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/tree-sitter/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How tree-sitter Compares
| Feature / Agent | tree-sitter | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
AST-based code analysis using tree-sitter. Use for parsing code structure, extracting symbols, finding patterns with tree-sitter queries, analyzing complexity, and understanding code architecture. Supports Python, JavaScript, TypeScript, Go, Rust, C, C++, Swift, Java, Kotlin, Julia, and more.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Tree-sitter Code Analysis
Intelligent code analysis via AST parsing with tree-sitter.
## When to Use
- Understanding code structure across multiple languages
- Extracting function/class definitions
- Finding code patterns with tree-sitter queries
- Analyzing code complexity
- Symbol extraction and dependency analysis
## Setup
MCP server configured in `~/.mcp.json`:
```json
{
"tree-sitter": {
"command": "python3",
"args": ["-m", "mcp_server_tree_sitter.server"],
"cwd": "/Users/alice/mcp-server-tree-sitter"
}
}
```
## Usage Pattern
### 1. Register a Project First
```
register_project_tool(path="/path/to/project", name="my-project")
```
### 2. Explore Files
```
list_files(project="my-project", pattern="**/*.py")
get_file(project="my-project", path="src/main.py")
```
### 3. Analyze Structure
```
get_ast(project="my-project", path="src/main.py", max_depth=3)
get_symbols(project="my-project", path="src/main.py")
```
### 4. Search with Queries
```
find_text(project="my-project", pattern="function", file_pattern="**/*.py")
run_query(
project="my-project",
query='(function_definition name: (identifier) @function.name)',
language="python"
)
```
### 5. Complexity Analysis
```
analyze_complexity(project="my-project", path="src/main.py")
```
## Available Tools
- **Project**: `register_project_tool`, `list_projects_tool`, `remove_project_tool`
- **Language**: `list_languages`, `check_language_available`
- **Files**: `list_files`, `get_file`, `get_file_metadata`
- **AST**: `get_ast`, `get_node_at_position`
- **Search**: `find_text`, `run_query`
- **Symbols**: `get_symbols`, `find_usage`
- **Analysis**: `analyze_project`, `get_dependencies`, `analyze_complexity`
- **Queries**: `get_query_template_tool`, `build_query`, `adapt_query`
- **Similar Code**: `find_similar_code`
## Supported Languages
Python, JavaScript, TypeScript, Go, Rust, C, C++, Swift, Java, Kotlin, Julia, APL, and many more via tree-sitter-language-pack.
## Scientific Skill Interleaving
This skill connects to the K-Dense-AI/claude-scientific-skills ecosystem:
### Tree Structures
- **etetoolkit** [○] via bicomodule
- Tree parsing and traversal
### Bibliography References
- `graph-theory`: 38 citations in bib.duckdb
## Cat# Integration
This skill maps to **Cat# = Comod(P)** as a bicomodule in the equipment structure:
```
Trit: 0 (ERGODIC)
Home: Prof
Poly Op: ⊗
Kan Role: Adj
Color: #26D826
```
### GF(3) Naturality
The skill participates in triads satisfying:
```
(-1) + (0) + (+1) ≡ 0 (mod 3)
```
This ensures compositional coherence in the Cat# equipment structure.