name	liteparse
description	Use this skill whenever a task involves a document file (PDF, DOCX, PPTX, XLSX, or image) and you need to read it or get text, tables, or specific values out of it — including to answer a question about its contents, look up a figure, extract data, or convert it to text/JSON. Provides fast, local, model-free extraction with no cloud or API key. Reach for this instead of ad-hoc pdftotext/pypdf/textract whenever a question or task references a document file.
compatibility	Requires Node 18+ and `@llamaindex/liteparse` installed globally (`npm i -g @llamaindex/liteparse`). LibreOffice for Office files; ImageMagick for images.
license	MIT
metadata	{"author":"LlamaIndex","version":"0.3.0"}

LiteParse

Extract text from documents locally with the lit CLI — a fast, model-free parser (a drop-in, faster replacement for pdftotext/pypdf).

Answering a question about ONE document: stream and search in a SINGLE shell command

lit parse writes plain text to stdout, so pipe it straight into your normal search tools in one Bash command — exactly how you would use pdftotext -layout file.pdf - | grep. Do not write an intermediate file, and do not use the Read or Grep tools on a saved file: each of those is an extra agent round-trip. Keep parse+search fused in one command:

lit parse ./input.pdf --format text --no-ocr | grep -i -n -A3 -B3 "total assets" | head -40
lit parse ./input.pdf --format text --no-ocr | sed -n '900,945p'

Born-digital PDF (has a real text layer): add --no-ocr — much faster, identical text.
Scanned PDF / image: drop --no-ocr (OCR on). If the value is missing from the OCR text or the digits look wrong, read the page visually instead of trusting OCR: render it with lit screenshot ./input.pdf --target-pages "N" -o ./shots/ and view the PNG.
Multi-column tables: piped --format text keeps most layout; if columns collapse so you can't tell which column a number is in, render that page and read it visually.

Answering MANY questions about the same document(s): parse once, reuse

Only here is it worth materializing a file (so you don't re-parse per question):

lit parse ./inputs/<doc>.pdf --format text --no-ocr -o ./parsed/<doc>.txt   # once per doc
grep -i -n -A3 -B3 "total assets" ./parsed/<doc>.txt                        # then search the file

Core flags

--format text|json · --no-ocr · --dpi <n> (default 150) · --target-pages "1-5,10" · --ocr-language <iso> · lit batch-parse ./in ./out. Use --format json only when you need bounding boxes / layout (it is much larger — still search it, don't load it whole).

Setup

PDF works out of the box. If lit is missing: npm i -g @llamaindex/liteparse (verify lit --version). Office docs need LibreOffice; images need ImageMagick (auto-converted to PDF).

LiteParse

Extract text from documents locally with the lit CLI — a fast, model-free parser (a drop-in, faster replacement for pdftotext/pypdf).

Answering a question about ONE document: stream and search in a SINGLE shell command

lit parse ./input.pdf --format text --no-ocr | grep -i -n -A3 -B3 "total assets" | head -40 lit parse ./input.pdf --format text --no-ocr | sed -n '900,945p'

Born-digital PDF (has a real text layer): add --no-ocr — much faster, identical text.

Scanned PDF / image: drop --no-ocr (OCR on). If the value is missing from the OCR text or the digits look wrong, read the page visually instead of trusting OCR: render it with lit screenshot ./input.pdf --target-pages "N" -o ./shots/ and view the PNG.

Multi-column tables: piped --format text keeps most layout; if columns collapse so you can't tell which column a number is in, render that page and read it visually.

Answering MANY questions about the same document(s): parse once, reuse

Only here is it worth materializing a file (so you don't re-parse per question):

lit parse ./inputs/<doc>.pdf --format text --no-ocr -o ./parsed/<doc>.txt # once per doc grep -i -n -A3 -B3 "total assets" ./parsed/<doc>.txt # then search the file

Core flags

Setup

PDF works out of the box. If lit is missing: npm i -g @llamaindex/liteparse (verify lit --version). Office docs need LibreOffice; images need ImageMagick (auto-converted to PDF).