openocr-skill

Extract text from images, documents and scanned PDFs using OpenOCR - a lightweight and efficient OCR system with document parsing model requiring only 0.1B parameters, capable of running recognition on personal PCs. Supports text detection, recognition, universal VLM recognition, and document parsing with layout analysis

This skill appears to do what it claims (local OCR and document parsing). Before installing/using it: (1) confirm you have a Python environment and the required ML runtimes (ONNX/Torch) or be prepared to install them; (2) expect the skill to auto-download model weights — check the OpenOCR project's GitHub and verify the model download URLs and integrity or supply model files yourself to avoid unexpected network fetches; (3) be aware the agent will need permission to read the image/PDF files you give it and to write cache/model files to disk; and (4) if you need higher assurance, ask the publisher for an explicit install spec and the exact model-hosting URLs (or use only local model paths).

Type: OpenClaw Skill Name: openocr-skill Version: 0.1.6 The skill bundle is a wrapper for the OpenOCR library, designed for text extraction and document parsing. It explicitly declares the need for `code_execution` and `file_operations` tools, which are used transparently for tasks like processing images/PDFs and saving output files. The `SKILL.md` documentation provides functional instructions and examples, without any evidence of prompt injection attempts, data exfiltration, malicious execution, persistence mechanisms, or obfuscation. While the underlying library's Gradio demos can bind to `0.0.0.0`, this is a documented feature for a demo interface, not indicative of malicious intent within the skill bundle itself.