According to AlphaMoat, as of 2026-09, PDF OCR Using Gemini LLM has 1,456 downloads and 0 stars — ranked #4,791 of 5,078 AI skills overall, and #393 of 435 in Office.

Installs

305

Downloads

1.5K

Stars

Overall Rank

#4,791

Top 95% overall · Top 91% in Office

Platform	Installs	Downloads	Stars	Comments
ClawHub ↗	23	926	-	-
SkillHub ↗	305	1.5K	-	—

Platforms count differently and update at different times.

What this skill does

It splits PDFs into pages and uploads them for OCR, requiring a Google API key and Python dependencies. Options limit pages, return text or JSON and write an output file. Approve external processing for the document, isolate dependencies and review output paths and extracted text.

Profile published 2026-10-27

What you can do with it

Extract text from an approved PDF

When to use it

When Google-based OCR is acceptable

Example prompts

Generated from the skill’s documentation as examples; not results of actual runs.

Plan OCR with a page limit and chosen output path, explaining the full-page upload.

Monthly Trend

Downloads1.5K

Stars-

The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.

Month	Downloads	MoM	Stars
2026-09	1.5K	—	-
2026-08	1.2K	+7.7%	-
2026-07	1.1K	+14.9%	-
2026-06	956	+9.9%	-
2026-05	870	—	-
2026-03	549	—	-

SKILL.md (original)

The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.

2.0 KB · ClawHub v0.1.7

---
name: PDF OCR using Gemini LLM
description: Extract text from PDFs using Google Gemini OCR. Use when extracting text from PDFs, performing OCR on scanned documents, or processing image-based PDFs.
metadata:
  openclaw:
    requires:
      env:
        - GOOGLE_API_KEY
    primaryEnv: GOOGLE_API_KEY
    install:

Show all (63 lines)

      - kind: uv
        package: google-genai
        label: "Python deps"
      - kind: uv
        package: pymupdf
      - kind: uv
        package: pydantic
      - kind: uv
        package: pydantic-settings
---

## Purpose

Use geminipdfocr to extract text from PDF documents via OCR (Google Gemini).

## Data and privacy

**Full page images/files are sent to Google's API.** PDFs are split into single-page files and each page is uploaded to Google Gemini for OCR. There are no hidden exfiltration endpoints or other data collection. Do not use with highly sensitive documents unless you accept that content is sent to Google.

## Setup (venv installation)

Before first use, create and activate the virtual environment:

```bash
cd geminipdfocr && python -m venv venv && source venv/bin/activate && pip install -r requirements.txt
```

Set `GOOGLE_API_KEY` in your environment before running (e.g. `export GOOGLE_API_KEY=your-key`).

## How to use

When requested to extract text or perform OCR on a PDF:

1. Run: `cd geminipdfocr && source venv/bin/activate && python -m geminipdfocr <path-to-pdf> [--json] [--output <file>]`
2. Use `--json` for structured data.
3. Use `--max-pages N` for testing or very long documents.
4. Use `--quiet` to suppress progress logs.

## Requirements

- A valid PDF file path.
- `GOOGLE_API_KEY` set in the process environment (e.g. `export GOOGLE_API_KEY=your-key`).

## CLI options

| Option | Description |
|--------|-------------|
| `pdf_path` | One or more PDF file paths (positional) |
| `--max-pages N` | Limit pages per PDF |
| `--json` | Output structured JSON instead of plain text |
| `--output FILE` | Write result to file (default: stdout) |
| `--quiet` | Suppress INFO/DEBUG logs |