Agent skill · data analytics · k-dense-ai
liteparse
Local document and PDF parsing that returns spatial text with bounding boxes. Use for extracting text from PDFs, DOCX, Office files, and images; running OCR on scans; producing layout-preserved JSON for RAG; batch-ingesting folders of papers; or rendering pages to PNG for multimodal agents. Distinguishing capabilities are per-token bounding boxes, page raster output, and fully local processing with no cloud API.
Why this skill is useful
Adds a local document parsing capability with spatial text extraction and bounding boxes that the AI cannot generate on its own.
What it needs
Requires imagemagick, libreoffice, liteparse installed locally. About 5k tokens when loaded. Last updated 2026-08-03. 32,849 stars on the source repository.
What this skill does
LiteParse — Local Document Parsing Overview LiteParse is a fast, open-source document parser (Rust core, Python/Node bindings) focused on local, layout-aware text extraction with bounding boxes. It does not produce Markdown and does not call cloud LLMs. Outputs are plain text (layout-preserved) or structured JSON with per-page textitems (position, font metadata, optional confidence). Version note: Examples target liteparse 2.0.0 (PyPI, May 2026). The upstream V1 branch is legacy; this skill documents V2 / main only. For parser selection vs MarkItDown, the pdf skill, or LlamaParse, see references/choosingaparser.md. When to Use This Skill Use LiteParse when you need: Fast local parsing of PDFs or converted Office/image files without cloud dependencies Spatial text with bounding boxes for layout-aware RAG, citation grounding, or figure/table region logic OCR on scanned PDFs or images (bundled Tesseract, or a user-run HTTP OCR server) Page screenshots (PNG) for multimodal agents that must see charts, figures, or handwriting Batch ingestion of literature folders, supplementary PDFs, or protocol libraries Page subsets or password-protected PDFs When Not to Use Task Use instead ------ ------------- Markdown for LLM ingestion (EPUB, audio, YouTube, HTML) markitdown skill Merge/split PDFs, forms, watermarks, rotation pdf skill Dense tables, handwriting, production cloud pipelines LlamaParse (cloud; sign up separately) Installation This installs the Python bindings and the lit CLI. Verify: Optional system tools (for non-PDF inputs): LibreOffice — Word, Excel, PowerPoint, OpenDocument, CSV/TSV ImageMagick — PNG, JPEG, TIFF, WebP, SVG, etc. Install commands are in references/ocrandformats.md. Node.js / TypeScript (optional): npm i @llamaindex/liteparse — see references/apireference.md. --- Quick Start Python CLI --- Core Workflows 1. Parse to layout-preserved text Best for quick full-document text or feeding chunkers that do not need coordinates. 2. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills k-dense-ai/liteparse