synthetic-sciences/openscience is an AI workbench that carries out scientific research by reading papers, forming hypotheses, writing and running code, conducting experiments, analyzing results, and preparing reports. Researchers use it for work in machine learning, biology, physics, and chemistry with remote or local models. Catalogue add-ons extend its scientific workflows through skills and instructions.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/synthetic-sciences/openscience/liteparsenpx skills add synthetic-sciences/openscience --skill liteparsegit clone --depth 1 https://github.com/synthetic-sciences/openscienceWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/synthetic-sciences/openscience/liteparse)<a href="https://agentmods.dev/skills/synthetic-sciences/openscience/liteparse"><img src="https://agentmods.dev/badge/skills/synthetic-sciences/openscience/liteparse.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00049 | $0.01478 |
| Opus 5 | $0.00024 | $0.00739 |
| Sonnet 5 | $0.00010 | $0.00296 |
| Haiku 4.5 | $0.00005 | $0.00148 |
Grade A, and why
liteparse scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LiteParse Skill
Parse unstructured documents (PDF, DOCX, PPTX, XLSX, images, and more) locally with LiteParse: fast, lightweight, no cloud dependencies or LLM required.
Initial Setup
When this skill is invoked, respond with:
I'm ready to use LiteParse to parse files locally. Before we begin, please confirm that:
- `@llamaindex/liteparse` is installed globally (`npm i -g @llamaindex/liteparse`)
- The `lit` CLI command is available in your terminal
If both are set, please provide:
1. One or more files to parse (PDF, DOCX, PPTX, XLSX, images, etc.)
2. Any specific options: output format (json/text), page ranges, OCR preferences, DPI, etc.
3. What you'd like to do with the parsed content.
I will produce the appropriate `lit` CLI command or TypeScript script, and once approved, report the results.
Then wait for the user's input.
Step 0 — Install LiteParse (if needed)
If liteparse is not yet installed, install it globally:
npm i -g @llamaindex/liteparse
Verify installation:
lit --version
For Office document support (DOCX, PPTX, XLSX), LibreOffice is required:
# macOS
brew install --cask libreoffice
# Ubuntu/Debian
apt-get install libreoffice
For image parsing, ImageMagick is required:
# macOS
brew install imagemagick
# Ubuntu/Debian
apt-get install imagemagick
Step 1 — Produce the CLI Command or Script
Parse a Single File
# Basic text extraction
lit parse document.pdf
# JSON output saved to a file
lit parse document.pdf --format json -o output.json
# Specific page range
lit parse document.pdf --target-pages "1-5,10,15-20"
# Disable OCR (faster, text-only PDFs)
lit parse document.pdf --no-ocr
# Use an external HTTP OCR server for higher accuracy
lit parse document.pdf --ocr-server-url http://localhost:8828/ocr
# Higher DPI for better quality
lit parse document.pdf --dpi 300
Batch Parse a Directory
lit batch-parse ./input-directory ./output-directory
# Only process PDFs, recursively
lit batch-parse ./input ./output --extension .pdf --recursive
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 223 lines · 49 tokens per session scan A 9da9795b5846
liteparse is a skill published in the GitHub repository synthetic-sciences/openscience (3,473 stars, last pushed today), licensed Apache-2.0. It adds 49 tokens to every session and 1,478 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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