Liteparse

What it does

When your agent uses it

• Extracting text from PDFs
• Running OCR on scans
• Producing layout-preserved JSON for RAG
• Batch-ingesting folders of papers

Example prompts

• “/liteparse”

Requirements

• Python 3
• Node.js
• Compatibility (from SKILL.md): Python 3.10+ with liteparse 2.15.0. LibreOffice required for Office formats; images convert natively. Tesseract is bundled but missing language data downloads on first use. Optional HTTP OCR requires network access and server-specific authentication.
• Pre-approved tools (allowed-tools): Read, Write, Edit, Bash

Workflow steps

9 steps, taken from the step headings in SKILL.md.

1. 1Parse to layout-preserved text
2. 2Parse to structured JSON (bounding boxes)
3. 3Parse specific pages
4. 4Parse from bytes or stdin
5. 5Page screenshots for multimodal agents
6. 6Batch-parse a directory
7. 7OCR configuration
8. 8Encrypted PDFs
9. 9Search text items by phrase

What it can do on your machine

Read from SKILL.md and the folder at commit 92ace75. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves these tools, so the agent can use them without asking each time:

  • Read
  • Write
  • Edit
  • Bash

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships 1 file in scripts/ (Python), which the agent can run.

  Shell commands in SKILL.md call:

  • python
  • uv
  • curl
  • npm

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Links to these hosts (documentation or services it may open):

  • developers.llamaindex.ai
  • github.com
  • arxiv.org
  • pypi.org
  • npmjs.com
  • doi.org
  • export.arxiv.org

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

• Compatibility

  Python 3.10+ with liteparse 2.15.0. LibreOffice required for Office formats; images convert natively. Tesseract is bundled but missing language data downloads on first use. Optional HTTP OCR requires network access and server-specific authentication.

  From compatibility in the SKILL.md frontmatter.

Context cost

Liteparse loads about 3.1k tokens when it runs, and up to ~9.7k if it reads all its reference files. Until then it costs about 108 tokens; SKILL.md has 1,003 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~108

When it runs · the whole SKILL.md, loaded when a task matches

~3.1k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~9.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

• NotePre-approves every shell command (allowed-tools: Bash)SKILL.md

  allowed-tools: Read, Write, Edit, Bash

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from K-Dense-AI/scientific-agent-skills at commit 92ace75, republished under its Apache-2.0 licence (© K-Dense-AI). 1,003 words, ~3,090 tokens.

name

liteparse

description

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.

allowed-tools

Read, Write, Edit, Bash

compatibility

Python 3.10+ with liteparse 2.15.0. LibreOffice required for Office formats; images convert natively. Tesseract is bundled but missing language data downloads on first use. Optional HTTP OCR requires network access and server-specific authentication.

license

Apache-2.0

metadata.version

1.6

metadata.last-reviewed

2026-10-01

metadata.upstream-version

2.15.0

metadata.skill-author

K-Dense Inc.

uv pip install "liteparse==2.15.0"

lit --help
python -c "import liteparse; print(liteparse.__version__)"

from liteparse import LiteParse

parser = LiteParse(quiet=True)
result = parser.parse("paper.pdf")
print(result.text)

for page in result.pages:
    print(f"Page {page.page_num}: {len(page.text_items)} items")

# Layout-preserved text (default)
lit parse paper.pdf

# Structured JSON with bounding boxes
lit parse paper.pdf --format json -o paper.json

# Heuristic Markdown, including headings, tables and links
lit parse paper.pdf --format markdown -o paper.md

# Disable OCR on text-native PDFs (faster)
lit parse paper.pdf --no-ocr

parser = LiteParse(ocr_enabled=True, quiet=True)
result = parser.parse("document.pdf")
full_text = result.text

lit parse document.pdf -o output.txt

from liteparse import LiteParse

parser = LiteParse(output_format="json", quiet=True)
result = parser.parse("document.pdf")

# Programmatic access
for page in result.pages:
    for item in page.text_items:
        bbox = (item.x, item.y, item.width, item.height)
        # item.text, item.confidence, item.font_name, item.font_size

lit parse document.pdf --format json -o document.json

parser = LiteParse(target_pages="1-5,10,15-20", quiet=True)
result = parser.parse("long_paper.pdf")

lit parse long_paper.pdf --target-pages "1-5,10"

with open("document.pdf", "rb") as f:
    result = parser.parse(f.read())

curl -sL https://example.com/report.pdf | lit parse -

from pathlib import Path

parser = LiteParse(dpi=150, quiet=True)
shots = parser.screenshot("document.pdf", page_numbers=[1, 2, 3])
out = Path("screenshots")
out.mkdir(exist_ok=True)
for s in shots:
    (out / f"page_{s.page_num}.png").write_bytes(s.image_bytes)

lit screenshot document.pdf --target-pages "1,3,5" -o ./screenshots
lit screenshot document.pdf --dpi 300 -o ./screenshots

lit batch-parse ./papers ./parsed --format json --recursive
lit batch-parse ./papers ./parsed --extension .pdf --no-ocr

python scripts/batch_parse_dir.py ./papers ./parsed --format json --recursive

parser = LiteParse(
    ocr_enabled=True,
    ocr_language="eng",       # Tesseract codes: fra, deu, etc.
    num_workers=4,            # parallel OCR (default: CPU cores - 1)
    dpi=150,                  # higher DPI → better OCR, slower
)

lit parse scan.pdf --ocr-language fra
lit parse scan.pdf --no-ocr
lit parse scan.pdf --ocr-server-url http://localhost:8080/ocr

parser = LiteParse(password="secret", quiet=True)
result = parser.parse("protected.pdf")

lit parse protected.pdf --password secret

from liteparse import search_items

page = result.get_page(1)
matches = search_items(page.text_items, "Materials and Methods", case_sensitive=False) if page else []

© K-Dense-AI, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (scripts, references) in skills/liteparse of K-Dense-AI/scientific-agent-skills.

• SKILL.md
• references/api_reference.md
• references/choosing_a_parser.md
• references/cli_reference.md
• references/ocr_and_formats.md
• references/output_formats.md
• scripts/batch_parse_dir.py

Open the folder on GitHubat commit 92ace75

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in K-Dense-AI/scientific-agent-skills, which our catalogue first saw on October 7, 2026.

• lingxling/awesome-skills-cnclaude-scientific-skills/skills/liteparse