tree-sitter-language-pack

SkillAI & models

Parse and extract code intelligence from 371 programming languages using tree-sitter grammars. Use when writing code that parses source, extracts structure/imports/exports/symbols/docstrings/comments, detects a language, runs syntax diagnostics, or produces syntax-aware chunks for LLMs — in Rust, Python, Node.js/TypeScript, or the ts-pack CLI. Covers installation, the CLI surface, the SDK surface, and parser-cache management.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the tree-sitter-language-pack skill

What this skill tells your AI

The instructions your AI receives, as published by xberg-io/tree-sitter-language-pack in plugin/skills/tree-sitter-language-pack/SKILL.md and read by ahel’s review.

Tree-Sitter Language Pack

tree-sitter-language-pack is a polyglot code parsing and analysis library with a high-performance Rust core and polyglot bindings for 15 languages — Python, Node.js/TypeScript, Ruby, Go, Java, C#, PHP, Elixir, Dart, Kotlin (Android), Swift, Zig, and WebAssembly, plus a C ABI and JNI. It compiles 371 tree-sitter grammars into efficient parsers and exposes code intelligence on top of them.

Capabilities

  • Parse 371 languages into concrete syntax trees (s-expression or JSON).
  • Extract structure — functions, classes, methods, modules with line and byte spans, child nesting, and visibility.
  • Extract imports and exports — statements, sources, exported kinds.
  • Extract symbols — all identifiers, for search and indexing.
  • Extract docstrings and comments — attached to definitions or standalone.
  • Language detection — from a file path, an extension, or content.
  • Syntax diagnostics — error nodes and syntax errors with positions.
  • Syntax-aware chunking — split source on syntactic boundaries for LLM context windows, not on arbitrary byte offsets.
  • Custom tree-sitter queries — run your own query patterns over a tree (SDK only).
  • Parser cache management — download, list, inspect, and clean the on-demand parser cache for offline/CI use.
  • Distribution — 15 language bindings (including WebAssembly, a C ABI, and JNI) plus the ts-pack CLI.

Use this skill when writing code that parses source in any supported language, extracts code metadata, chunks code for an LLM, detects a language, or validates syntax.

When to use

Reach for tree-sitter-language-pack when you need a real syntax tree or structured code metadata — building a code index, feeding code to an LLM in semantically coherent chunks, linting for syntax errors across many languages, or detecting a file's language. For plain text extraction from documents (PDF, Office, HTML), use Xberg instead.

CLI vs SDK

  • CLI (ts-pack) — quick one-shot parsing and extraction over files, parser-cache management, and shell/CI pipelines. parse and process print to stdout (process always emits JSON). Auto-detects the language from the file extension.
  • SDK — embed parsing in an application, run custom tree-sitter queries, detect a language from raw content (not just a path), or hold parsers across many calls. Use the Rust core or the Python/Node bindings.
  • MCP server (ts-pack mcp) — exposes parse/process/detect_language (plus language and cache tools) as agent tools, so an MCP client can parse and analyze code directly with no shell-out. This plugin auto-registers it; see the using-the-mcp-server skill.

Prefer the CLI for ad-hoc work in an agent session; prefer the SDK when the result feeds back into a larger program; prefer the MCP server when the agent should call parsing directly as a tool.

Installation

CLI

brew install xberg-io/tap/ts-pack
# or run without a persistent install (the CLI proxy package self-installs the binary):
npx @xberg-io/ts-pack-cli --help
uvx --from ts-pack-cli ts-pack --help
# or download a prebuilt binary from the latest GitHub release:
#   https://github.com/xberg-io/tree-sitter-language-pack/releases/latest
# or install from crates.io:
cargo install ts-pack-cli
# binary is installed as `ts-pack`

Python

pip install tree-sitter-language-pack
# or: uv add tree-sitter-language-pack

Node.js / TypeScript

npm install @xberg-io/tree-sitter-language-pack
# or: pnpm add @xberg-io/tree-sitter-language-pack

Rust

# Cargo.toml
[dependencies]
tree-sitter-language-pack = { version = "1", features = ["download"] }

Other bindings: Ruby (gem install tree_sitter_language_pack), Go, Java, C#, PHP, Elixir, Dart, Kotlin (Android), Swift, Zig, and WebAssembly (npm install @xberg-io/tree-sitter-language-pack-wasm). See https://github.com/xberg-io/tree-sitter-language-pack.

CLI surface

ts-pack has these subcommands:

CommandPurpose
parse <file>Parse a file into a syntax tree (`--format sexp
process <file>Run the code-intelligence pipeline, emit JSON.
detect*No standalone command — parse/process auto-detect from the extension. Use the SDK for content detection.
listList available languages (--downloaded, --manifest, --filter).
info <language>Show whether a language is known and cached.
download [langs...]Download parser libraries (--all, --groups, --fresh).
cleanRemove all cached parser libraries (--force).
cache-dirPrint the effective cache directory.
initWrite a language-pack.toml config (--languages, --cache-dir).
completions <shell>Generate shell completions.
mcpStart the MCP server (--transport stdio).

* Language detection is implicit in parse/process. There is no detect or validate subcommand; diagnostics come from process --diagnostics.

Parse

ts-pack parse src/main.rs                 # s-expression tree (auto-detect)
ts-pack parse src/main.rs --format json   # { language, sexp, has_errors }
ts-pack parse - --language python         # read from stdin, explicit language

Process (code intelligence)

# Defaults to structure + imports + exports when no feature flags are given:
ts-pack process src/app.ts

# Pick features explicitly:
ts-pack process src/app.ts --structure --imports --symbols --docstrings

# Everything:
ts-pack process src/app.ts --all

# Syntax-aware chunks (bytes) for an LLM:
ts-pack process src/app.ts --chunk-size 2000

# Syntax diagnostics:
ts-pack process src/app.ts --diagnostics

process always prints JSON. Top-level keys: language, metrics, structure, imports, exports, comments, docstrings, symbols, diagnostics, and chunks (when --chunk-size is set).

SDK quick start

from tree_sitter_language_pack import process, ProcessConfig, detect_language_from_path

config = ProcessConfig("python", symbols=True, docstrings=True)  # structure/imports/exports default to True
result = process(source_code, config)
for item in result.structure:                 # ProcessResult is an object, not a dict
    print(item.kind, item.name, item.span.start_line)

# Path-based detection (use detect_language_from_content for raw text;
# see the detecting-languages skill):
lang = detect_language_from_path("src/app.py")
import { process, detectLanguageFromPath } from "@xberg-io/tree-sitter-language-pack";

const lang = detectLanguageFromPath("src/app.ts");
const result = process(source, { language: lang ?? "typescript", structure: true, imports: true });

Parser cache

Parsers download on demand the first time a language is used and are cached locally. For offline or CI runs, prefetch:

ts-pack download python rust typescript   # specific languages
ts-pack download --all                    # everything
ts-pack download --groups all             # by group (see manifest_groups())
ts-pack list --downloaded                 # what is cached
ts-pack cache-dir                         # where the cache lives
ts-pack clean --force                     # wipe the cache

See the managing-parsers skill for the full cache workflow.

Related skills

  • parsing-source — parse a file into a syntax tree / s-expression.
  • extracting-code-structureprocess with structure/imports/exports/ symbols/docstrings.
  • chunking-for-llms--chunk-size syntax-aware splitting.
  • detecting-languages — detect by path, extension, or content.
  • managing-parsers — download/clean/list/info parser-cache management.
  • using-the-mcp-server — call parse/process/detect_language over MCP instead of the CLI.

Full documentation: https://github.com/xberg-io/tree-sitter-language-pack

Signals

GitHub stars
465
Forks
68
Last commit
Sep 2026

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skill
Gateway key
tree-sitter-language-pack
Source
github.com/xberg-io/tree-sitter-language-pack