Menú
De forma predeterminada está seleccionado el prompt que primero revisa el origen. Puedes cambiar a un comando directo o descargar una copia local.
Lee SKILL.md y los archivos complementarios que muestra SkillsMP antes de decidir si quieres instalarlo.
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
Un comando directo omite el prompt de revisión. Revisa el origen antes de ejecutarlo.
npx skills add https://github.com/lamm-mit/scienceclaw --skill pdfEl comando permanece en una sola línea. Desplázate horizontalmente para revisarlo antes de copiarlo.
¿Prefieres una copia local? Descarga los archivos que SkillsMP tiene disponibles ahora.
Onboard and manage Paperclip AI for research-paper knowledge and agent orchestration
Generate a structured scientific post and publish it to Infinite. Runs a focused single-agent investigation (PubMed search → LLM analysis → hypothesis/method/findings/conclusion) and posts the result. Faster than scienceclaw-investigate — best for targeted, single-topic posts.
Infinite platform integration for AI agent collaboration
Basado en la clasificación ocupacional SOC
Mostrando SKILL.md
| name | |
| description | Extract text, tables, and metadata from scientific PDF papers and reports |
| metadata | null |
PDF processing toolkit for extracting text, tables, and metadata from scientific papers, supplementary data files, and technical reports. Uses pdfplumber for high-fidelity text and table extraction with layout preservation, falling back to pypdf when pdfplumber is unavailable.
Supports page range selection for large documents and targeted extraction modes (text-only, tables-only, metadata-only) for efficient processing.
# Extract everything from a PDF
python3 skills/pdf/scripts/pdf_extract.py --file /path/to/paper.pdf
# Extract only text from pages 1-5
python3 skills/pdf/scripts/pdf_extract.py --file /path/to/paper.pdf --pages "1-5" --extract text
# Extract tables only
python3 skills/pdf/scripts/pdf_extract.py --file /path/to/supplementary.pdf --extract tables
# Extract metadata only
python3 skills/pdf/scripts/pdf_extract.py --file /path/to/paper.pdf --extract metadata
{
"file": "/path/to/paper.pdf",
"text": "Abstract\n\nWe present a novel approach to protein structure...",
"tables": [
[["Gene", "Expression", "p-value"], ["BRCA1", "2.4x", "0.001"]],
[["Compound", "IC50 (nM)"], ["Compound A", "12.3"]]
],
"metadata": {
"title": "Novel Approach to Protein Structure Prediction",
"author": "Smith et al.",
"creation_date": "2024-01-15",
"pages": 12
},
"page_count": 12
}
Install with pip:
pip install pdfplumber pypdf