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liteparse

k-dense-ai/scie…t-skills

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 spatial text boxes, Markdown, page raster output, and local parsing with optional custom HTTP OCR.

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安装命令

npx skills add https://github.com/k-dense-ai/scientific-agent-skills --skill liteparse

SKILL.md

LiteParse — Local Document Parsing

Overview

LiteParse is an open-source document parser (Rust core, Python/Node bindings) for local, layout-aware text extraction. It produces layout text, structured JSON, or heuristic Markdown. Spatial text items may span several words; Python emit_word_boxes=True adds word boxes when needed.

Verified release: Python liteparse 2.15.0 (September 29, 2026); CLI and synthetic local PDF/image fixtures tested on Python 3.13. Node/Rust examples below are source-checked and illustrative. Images convert through bundled Rust libraries, not ImageMagick. No cloud account is needed, but missing Tesseract language data can download from GitHub and an explicitly configured HTTP OCR service receives document images.

For parser selection vs MarkItDown, PDF manipulation libraries, or LlamaParse, see references/choosing_a_parser.md.

When to Use This Skill

Use LiteParse when you need:

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