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Install in OpenClaw
/install rapidocr
Description
Extract text from local image files with RapidOCR. Use when the user wants OCR on a JPG, PNG, WEBP, BMP, or TIFF image and may want plain text or JSON output.
Usage Guidance
This skill appears to be what it says: a local OCR wrapper that runs a Python RapidOCR engine. Before installing, verify you are comfortable installing the Python packages (rapidocr, onnxruntime) into your environment. Note the wrapper will search several environment variables (SKILL_* and common prompt/args names) and any JSON-like input for a local file path — that is by design to find an image path, but if you have sensitive values in those env vars you may want to clear them or run the skill in a clean environment. The wrapper only operates on existing local image files (it checks file extensions and existence) and does not include remote network calls or credential exfiltration. If you need stronger guarantees, review the included run_rapidocr.js and run_rapidocr.py code locally before use and run the skill in a restricted environment (container or isolated account) when trying it for the first time.
Capability Assessment
Purpose & Capability
Name/description, required binaries (node + a Python interpreter), and included files (JS wrapper + Python entrypoint) align with a local OCR wrapper that calls the RapidOCR Python library. The skill asks users to pip install 'rapidocr' and 'onnxruntime', which is consistent with the declared functionality.
Instruction Scope
The SKILL.md and wrapper focus on extracting a local image path and running the Python OCR engine. The wrapper enforces file-extension checks and existence (fs.existsSync) and explicitly forbids remote URLs and PDFs. Minor note: the wrapper will inspect a number of environment variables (SKILL_ARGS, SKILL_INPUT, SKILL_USER_PROMPT, INPUT, USER_PROMPT, ARGS, ARGUMENTS, PROMPT) and parse JSON-like input to find a local path. That behavior is coherent with its goal of locating a path from different input forms, but the SKILL metadata did not declare these env sources; users should be aware the wrapper reads them to extract the image path.
Install Mechanism
There is no install spec (instruction-only install), which is low-risk. The skill includes local code files (JS + Python) and instructs the user to install Python packages (rapidocr, onnxruntime) into their chosen interpreter. No downloads from external ad-hoc URLs or archive extraction are present.
Credentials
The skill does not request or require secrets/credentials. It does, however, read several environment variables as input sources and supports an override RAPIDOCR_PYTHON to choose the interpreter. These env vars are used only to find an image path or the Python binary and are not used to access unrelated credentials. Users should consider whether any of those env variables in their environment contain sensitive data (e.g., a prompt or path they don't want used).
Persistence & Privilege
The skill is not always-enabled, is user-invocable, and does not request persistent platform privileges or modify other skills. It runs as a wrapper that spawns a local Python process; there is no evidence it modifies system or agent-wide configuration.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install rapidocr - After installation, invoke the skill by name or use
/rapidocr - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.3
**Summary:** RapidOCR skill v1.0.3 introduces a new Node.js wrapper and updates usage instructions for improved clarity and reliability.
- Added a wrapper script (`run_rapidocr.py`) for orchestrating OCR tasks via Node.js.
- Updated documentation to focus on local image OCR only; dropped support details for remote URLs and PDFs.
- Streamlined command execution and output handling (plain text or JSON).
- Clarified dependency and installation instructions for easier troubleshooting.
- Improved guidance on when and how to use the skill.
v1.0.1
RapidOCR 1.0.1 introduces Node.js script support and flexible input parsing:
- Added new script file: run_rapidocr.js for enhanced input handling.
- Now accepts raw user instructions and auto-extracts image paths or URLs.
- Supports both local and remote image OCR; remote images are auto-downloaded.
- JSON output mode triggered by keywords (e.g., “返回json”, “--json”).
- Command-line invocation is now standardized via Node.js, improving OS compatibility and fallback handling.
v1.0.0
- Initial release of RapidOCR Skill, bringing the official RapidOCR CLI to ClawHub.
- Supports Chinese-English mixed OCR text recognition for local JPG, PNG, and WEBP images.
- No complex configuration required—simple one-click terminal usage.
- Returns structured recognized text, location coordinates, and confidence scores.
- Provides options for confidence filtering, visual bounding box output, and image orientation classification.
- Includes comprehensive user guide, examples, key usage tips, and FAQ.
Metadata
Frequently Asked Questions
What is RapidOCR?
Extract text from local image files with RapidOCR. Use when the user wants OCR on a JPG, PNG, WEBP, BMP, or TIFF image and may want plain text or JSON output. It is an AI Agent Skill for Claude Code / OpenClaw, with 182 downloads so far.
How do I install RapidOCR?
Run "/install rapidocr" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is RapidOCR free?
Yes, RapidOCR is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does RapidOCR support?
RapidOCR is cross-platform and runs anywhere OpenClaw / Claude Code is available (macos, linux, windows).
Who created RapidOCR?
It is built and maintained by RapidAI (@rapidai); the current version is v1.0.3.
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