Is there a page limit for document processing?

Yes, the skill supports PDF documents up to 1,000 pages long, with a fixed cost of 258 tokens per page regardless of content density.

Do I need a specific API key for this skill?

Yes, you must provide a GEMINI_API_KEY from Google AI Studio. This can be configured via environment variables or a local .env file within your project.

What types of files can this skill process?

This skill is optimized for PDF documents, utilizing Gemini's native vision capabilities to understand layout and visual elements. Text-only formats like TXT and Markdown are also supported.

How does it handle files larger than 20MB?

For files exceeding 20MB, the skill automatically switches from inline encoding to the Google File API, ensuring reliable processing of large documents.

Gemini Document Processing

Name: Gemini Document Processing
Author: nodays-off

bynodays-off

数据科学与机器学习

Integrates Google Gemini's native vision capabilities to analyze, summarize, and extract structured data from complex PDF documents.

关于

Gemini Document Processing is a specialized skill designed to leverage Google Gemini's multimodal power for high-fidelity document analysis. Unlike standard OCR, this skill understands the visual context of PDFs—including charts, tables, diagrams, and images—for up to 1,000 pages. It is ideal for developers needing to automate data extraction into validated JSON formats, generate context-aware summaries of long reports, or build intelligent Q&A systems on top of unstructured documentation. With built-in support for both small inline files and large documents via the Google File API, it provides a robust framework for professional-grade document intelligence pipelines.

主要功能

Native PDF vision processing for documents up to 1,000 pages
0 GitHub stars
Context-aware summarization and document-based Q&A
Automated handling of large files (>20MB) via Google File API
Multimodal understanding of charts, diagrams, and complex layouts
Structured data extraction with Pydantic and JSON schema validation

使用场景

Creating automated executive summaries for high-volume research or financial reports
Extracting specific fields from invoices, resumes, and medical forms into structured databases
Converting complex technical manuals or legal contracts into clean Markdown or HTML

关于

主要功能

Native PDF vision processing for documents up to 1,000 pages
0 GitHub stars
Context-aware summarization and document-based Q&A
Automated handling of large files (>20MB) via Google File API
Multimodal understanding of charts, diagrams, and complex layouts
Structured data extraction with Pydantic and JSON schema validation

使用场景

Creating automated executive summaries for high-volume research or financial reports
Extracting specific fields from invoices, resumes, and medical forms into structured databases
Converting complex technical manuals or legal contracts into clean Markdown or HTML