Individual skill
liteparse
Parse local document files into LLM-ready content on the daemon itself — PDFs → Markdown / structured JSON (with bounding boxes) / page screenshots via the bundled `lit` CLI. PDF works out of the box, offline, zero external deps (Tesseract + PDFium are bundled): digital PDFs use a near-instant native text path (`--no-ocr`), scanned PDFs fall back to bundled OCR. Image files (PNG/JPG) additionally need ImageMagick, and Office files (DOCX/XLSX/PPTX) need LibreOffice — install those on demand only when required. Use whenever the user attaches or points to a local file that must be read before reasoning, or asks to extract text / tables / page images from a file on disk. For web URLs and search, use the `ingest` skill instead.
sdk/cloud/catalog/skills/liteparse/SKILL.md
Source commit f83b859a173802a73d978197e92328ab2bf57a6e
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- Observed behavior
- Network or broad shell
- Last checked
- Nov 9, 2026
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- 1,364
- Repository last updated
- Oct 22, 2026
- License
- MIT
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# LiteParse (local-first document parsing)
LiteParse turns document files into text the model can read — **on the
daemon machine, offline, zero cloud dependency**. It ships as the
`@llamaindex/liteparse` npm package (CLI: `lit`) with **PDFium and
Tesseract bundled inside the package** — the digital-PDF and scanned-OCR
paths need no external system dependencies.
> Upstream: [`run-llama/liteparse`](https://github.com/run-llama/liteparse)
> + skill [`run-llama/llamaparse-agent-skills`](https://github.com/run-llama/llamaparse-agent-skills/blob/main/skills/liteparse/SKILL.md).
> Apache-2.0 (core) / MIT (skill), © LlamaIndex. Vendored as a Prismer
> built-in.
## Capability tiers — what works where